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Diffstat (limited to 'docs')
| -rw-r--r-- | docs/Changelog.md | 44 | ||||
| -rw-r--r-- | docs/FAQ.md | 422 | ||||
| -rw-r--r-- | docs/INSTALL.md | 245 | ||||
| -rw-r--r-- | docs/QuickStartGuide.md | 50 | ||||
| -rw-r--r-- | docs/afl-fuzz_approach.md | 543 | ||||
| -rw-r--r-- | docs/best_practices.md | 192 | ||||
| -rw-r--r-- | docs/binaryonly_fuzzing.md | 223 | ||||
| -rw-r--r-- | docs/custom_mutators.md | 123 | ||||
| -rw-r--r-- | docs/docs2.md | 124 | ||||
| -rw-r--r-- | docs/env_variables.md | 1013 | ||||
| -rw-r--r-- | docs/features.md | 61 | ||||
| -rw-r--r-- | docs/fuzzing_binary-only_targets.md | 296 | ||||
| -rw-r--r-- | docs/fuzzing_in_depth.md | 861 | ||||
| -rw-r--r-- | docs/ideas.md | 57 | ||||
| -rw-r--r-- | docs/important_changes.md | 58 | ||||
| -rw-r--r-- | docs/life_pro_tips.md | 87 | ||||
| -rw-r--r-- | docs/parallel_fuzzing.md | 259 | ||||
| -rw-r--r-- | docs/perf_tips.md | 209 | ||||
| -rw-r--r-- | docs/rpc_statsd.md | 267 | ||||
| -rw-r--r-- | docs/sister_projects.md | 319 | ||||
| -rw-r--r-- | docs/status_screen.md | 444 | ||||
| -rw-r--r-- | docs/technical_details.md | 550 | ||||
| -rw-r--r-- | docs/third_party_tools.md | 57 | ||||
| -rw-r--r-- | docs/tutorials.md | 30 |
24 files changed, 3346 insertions, 3188 deletions
diff --git a/docs/Changelog.md b/docs/Changelog.md index 0ffbef05..34b9affb 100644 --- a/docs/Changelog.md +++ b/docs/Changelog.md @@ -9,16 +9,46 @@ Want to stay in the loop on major new features? Join our mailing list by sending a mail to <afl-users+subscribe@googlegroups.com>. ### Version ++3.15a (dev) + - documentation restructuring, made possible by Google Season of Docs + - new binary-only fuzzing mode: coresight_mode for aarch64 CPUs :) + thanks to RICSecLab submitting! + - if instrumented libaries are dlopen()'ed after the forkserver you + will now see crashes. before you would have colliding coverage. + we changed this to force fixing a broken setup rather then allowing + ineffective fuzzing. + See docs/best_practices.md how to fix such setups. - afl-fuzz: - - added AFL_IGNORE_PROBLEMS plus checks to identify and abort on - incorrect LTO usage setups and enhanced the READMEs for better - information on how to deal with instrumenting libraries + - cmplog binaries will need to be recompiled for this version + (it is better!) - fix a regression introduced in 3.10 that resulted in less coverage being detected. thanks to Collin May for reporting! - + - added AFL_IGNORE_PROBLEMS, plus checks to identify and abort on + incorrect LTO usage setups and enhanced the READMEs for better + information on how to deal with instrumenting libraries + - fix -n dumb mode (nobody should use this) + - fix stability issue with LTO and cmplog + - better banner + - more effective cmplog mode + - more often update the UI when in input2stage mode + - frida_mode: + - better performance, bug fixes + - David Carlier added Android support :) + - afl-showmap, afl-tmin and afl-analyze: + - honor persistent mode for more speed. thanks to dloffre-snl + for reporting! + - fix bug where targets are not killed on timeouts + - moved hidden afl-showmap -A option to -H to be used for + coresight_mode + - Prevent accidently killing non-afl/fuzz services when aborting + afl-showmap and other tools. - afl-cc: + - new cmplog mode (incompatible with older afl++ versions) + - support llvm IR select instrumentation for default PCGUARD and LTO - fix for shared linking on MacOS - - llvm and LTO mode verified to work with new llvm 14-dev + - fixed a potential crash in targets for LAF string handling + - added AFL_USE_TSAN thread sanitizer support + - llvm and LTO mode modified to work with new llvm 14-dev (again) + - fix for AFL_REAL_LD - added the very good grammar mutator "GramaTron" to the custom_mutators - added optimin, a faster and better corpus minimizer by @@ -30,7 +60,7 @@ sending a mail to <afl-users+subscribe@googlegroups.com>. - fix AFL_PRELOAD issues on MacOS - removed utils/afl_frida because frida_mode/ is now so much better - added uninstall target to makefile (todo: update new readme!) - + - removed indirections in rust callbacks for unicornafl ### Version ++3.14c (release) - afl-fuzz: @@ -2748,7 +2778,7 @@ sending a mail to <afl-users+subscribe@googlegroups.com>. - Updated the documentation and added notes_for_asan.txt. Based on feedback from Hanno Boeck, Ben Laurie, and others. - - Moved the project to http://lcamtuf.coredump.cx/afl/. + - Moved the project to https://lcamtuf.coredump.cx/afl/. ### Version 0.46b: diff --git a/docs/FAQ.md b/docs/FAQ.md index 0e816062..7869ee61 100644 --- a/docs/FAQ.md +++ b/docs/FAQ.md @@ -1,243 +1,185 @@ -# Frequently asked questions about AFL++ - -## Contents - - * [What is the difference between AFL and AFL++?](#what-is-the-difference-between-afl-and-afl) - * [I got a weird compile error from clang](#i-got-a-weird-compile-error-from-clang) - * [How to improve the fuzzing speed?](#how-to-improve-the-fuzzing-speed) - * [How do I fuzz a network service?](#how-do-i-fuzz-a-network-service) - * [How do I fuzz a GUI program?](#how-do-i-fuzz-a-gui-program) - * [What is an edge?](#what-is-an-edge) - * [Why is my stability below 100%?](#why-is-my-stability-below-100) - * [How can I improve the stability value?](#how-can-i-improve-the-stability-value) +# Frequently asked questions (FAQ) If you find an interesting or important question missing, submit it via -[https://github.com/AFLplusplus/AFLplusplus/issues](https://github.com/AFLplusplus/AFLplusplus/issues) - -## What is the difference between AFL and AFL++? - -American Fuzzy Lop (AFL) was developed by Michał "lcamtuf" Zalewski starting in -2013/2014, and when he left Google end of 2017 he stopped developing it. - -At the end of 2019 the Google fuzzing team took over maintenance of AFL, however -it is only accepting PRs from the community and is not developing enhancements -anymore. - -In the second quarter of 2019, 1 1/2 year later when no further development of -AFL had happened and it became clear there would none be coming, AFL++ -was born, where initially community patches were collected and applied -for bug fixes and enhancements. Then from various AFL spin-offs - mostly academic -research - features were integrated. This already resulted in a much advanced -AFL. - -Until the end of 2019 the AFL++ team had grown to four active developers which -then implemented their own research and features, making it now by far the most -flexible and feature rich guided fuzzer available as open source. -And in independent fuzzing benchmarks it is one of the best fuzzers available, -e.g. [Fuzzbench Report](https://www.fuzzbench.com/reports/2020-08-03/index.html) - -## I got a weird compile error from clang - -If you see this kind of error when trying to instrument a target with afl-cc/ -afl-clang-fast/afl-clang-lto: -``` -/prg/tmp/llvm-project/build/bin/clang-13: symbol lookup error: /usr/local/bin/../lib/afl//cmplog-instructions-pass.so: undefined symbol: _ZNK4llvm8TypeSizecvmEv -clang-13: error: unable to execute command: No such file or directory -clang-13: error: clang frontend command failed due to signal (use -v to see invocation) -clang version 13.0.0 (https://github.com/llvm/llvm-project 1d7cf550721c51030144f3cd295c5789d51c4aad) -Target: x86_64-unknown-linux-gnu -Thread model: posix -InstalledDir: /prg/tmp/llvm-project/build/bin -clang-13: note: diagnostic msg: -******************** -``` -Then this means that your OS updated the clang installation from an upgrade -package and because of that the AFL++ llvm plugins do not match anymore. - -Solution: `git pull ; make clean install` of AFL++ - -## How to improve the fuzzing speed? - - 1. Use [llvm_mode](../instrumentation/README.llvm.md): afl-clang-lto (llvm >= 11) or afl-clang-fast (llvm >= 9 recommended) - 2. Use [persistent mode](../instrumentation/README.persistent_mode.md) (x2-x20 speed increase) - 3. Use the [AFL++ snapshot module](https://github.com/AFLplusplus/AFL-Snapshot-LKM) (x2 speed increase) - 4. If you do not use shmem persistent mode, use `AFL_TMPDIR` to put the input file directory on a tempfs location, see [docs/env_variables.md](docs/env_variables.md) - 5. Improve Linux kernel performance: modify `/etc/default/grub`, set `GRUB_CMDLINE_LINUX_DEFAULT="ibpb=off ibrs=off kpti=off l1tf=off mds=off mitigations=off no_stf_barrier noibpb noibrs nopcid nopti nospec_store_bypass_disable nospectre_v1 nospectre_v2 pcid=off pti=off spec_store_bypass_disable=off spectre_v2=off stf_barrier=off"`; then `update-grub` and `reboot` (warning: makes the system less secure) - 6. Running on an `ext2` filesystem with `noatime` mount option will be a bit faster than on any other journaling filesystem - 7. Use your cores! [README.md:3.b) Using multiple cores/threads](../README.md#b-using-multiple-coresthreads) - -## How do I fuzz a network service? - -The short answer is - you cannot, at least not "out of the box". - -Using a network channel is inadequate for several reasons: -- it has a slow-down of x10-20 on the fuzzing speed -- it does not scale to fuzzing multiple instances easily, -- instead of one initial data packet often a back-and-forth interplay of packets is needed for stateful protocols (which is totally unsupported by most coverage aware fuzzers). - -The established method to fuzz network services is to modify the source code -to read from a file or stdin (fd 0) (or even faster via shared memory, combine -this with persistent mode [instrumentation/README.persistent_mode.md](../instrumentation/README.persistent_mode.md) -and you have a performance gain of x10 instead of a performance loss of over -x10 - that is a x100 difference!). - -If modifying the source is not an option (e.g. because you only have a binary -and perform binary fuzzing) you can also use a shared library with AFL_PRELOAD -to emulate the network. This is also much faster than the real network would be. -See [utils/socket_fuzzing/](../utils/socket_fuzzing/). - -There is an outdated AFL++ branch that implements networking if you are -desperate though: [https://github.com/AFLplusplus/AFLplusplus/tree/networking](https://github.com/AFLplusplus/AFLplusplus/tree/networking) - -however a better option is AFLnet ([https://github.com/aflnet/aflnet](https://github.com/aflnet/aflnet)) -which allows you to define network state with different type of data packets. - -## How do I fuzz a GUI program? - -If the GUI program can read the fuzz data from a file (via the command line, -a fixed location or via an environment variable) without needing any user -interaction then it would be suitable for fuzzing. - -Otherwise it is not possible without modifying the source code - which is a -very good idea anyway as the GUI functionality is a huge CPU/time overhead -for the fuzzing. - -So create a new `main()` that just reads the test case and calls the -functionality for processing the input that the GUI program is using. - -## What is an "edge"? - -A program contains `functions`, `functions` contain the compiled machine code. -The compiled machine code in a `function` can be in a single or many `basic blocks`. -A `basic block` is the largest possible number of subsequent machine code -instructions that has exactly one entrypoint (which can be be entered by multiple other basic blocks) -and runs linearly without branching or jumping to other addresses (except at the end). -``` -function() { - A: - some - code - B: - if (x) goto C; else goto D; - C: - some code - goto E - D: - some code - goto B - E: - return -} -``` -Every code block between two jump locations is a `basic block`. - -An `edge` is then the unique relationship between two directly connected `basic blocks` (from the -code example above): -``` - Block A - | +[https://github.com/AFLplusplus/AFLplusplus/discussions](https://github.com/AFLplusplus/AFLplusplus/discussions). + +## General + +<details> + <summary id="what-is-the-difference-between-afl-and-aflplusplus">What is the difference between AFL and AFL++?</summary><p> + + AFL++ is a superior fork to Google's AFL - more speed, more and better + mutations, more and better instrumentation, custom module support, etc. + + American Fuzzy Lop (AFL) was developed by Michał "lcamtuf" Zalewski starting + in 2013/2014, and when he left Google end of 2017 he stopped developing it. + + At the end of 2019, the Google fuzzing team took over maintenance of AFL, + however, it is only accepting PRs from the community and is not developing + enhancements anymore. + + In the second quarter of 2019, 1 1/2 years later, when no further development + of AFL had happened and it became clear there would none be coming, AFL++ was + born, where initially community patches were collected and applied for bug + fixes and enhancements. Then from various AFL spin-offs - mostly academic + research - features were integrated. This already resulted in a much advanced + AFL. + + Until the end of 2019, the AFL++ team had grown to four active developers + which then implemented their own research and features, making it now by far + the most flexible and feature rich guided fuzzer available as open source. And + in independent fuzzing benchmarks it is one of the best fuzzers available, + e.g., [Fuzzbench + Report](https://www.fuzzbench.com/reports/2020-08-03/index.html). +</p></details> + +<details> + <summary id="where-can-i-find-tutorials">Where can I find tutorials?</summary><p> + + We compiled a list of tutorials and exercises, see + [tutorials.md](tutorials.md). +</p></details> + +<details> + <summary id="what-is-an-edge">What is an "edge"?</summary><p> + + A program contains `functions`, `functions` contain the compiled machine code. + The compiled machine code in a `function` can be in a single or many `basic + blocks`. A `basic block` is the largest possible number of subsequent machine + code instructions that has exactly one entry point (which can be be entered by + multiple other basic blocks) and runs linearly without branching or jumping to + other addresses (except at the end). + + ``` + function() { + A: + some + code + B: + if (x) goto C; else goto D; + C: + some code + goto E + D: + some code + goto B + E: + return + } + ``` + + Every code block between two jump locations is a `basic block`. + + An `edge` is then the unique relationship between two directly connected + `basic blocks` (from the code example above): + + ``` + Block A + | + v + Block B <------+ + / \ | + v v | + Block C Block D --+ + \ v - Block B <------+ - / \ | - v v | - Block C Block D --+ - \ - v - Block E -``` -Every line between two blocks is an `edge`. -Note that a few basic block loop to itself, this too would be an edge. - -## Why is my stability below 100%? - -Stability is measured by how many percent of the edges in the target are -"stable". Sending the same input again and again should take the exact same -path through the target every time. If that is the case, the stability is 100%. - -If however randomness happens, e.g. a thread reading other external data, -reaction to timing, etc. then in some of the re-executions with the same data -the edge coverage result will be different accross runs. -Those edges that change are then flagged "unstable". - -The more "unstable" edges, the more difficult for AFL++ to identify valid new -paths. - -A value above 90% is usually fine and a value above 80% is also still ok, and -even a value above 20% can still result in successful finds of bugs. -However, it is recommended that for values below 90% or 80% you should take -countermeasures to improve stability. - -## How can I improve the stability value? - -For fuzzing a 100% stable target that covers all edges is the best case. -A 90% stable target that covers all edges is however better than a 100% stable -target that ignores 10% of the edges. - -With instability you basically have a partial coverage loss on an edge, with -ignored functions you have a full loss on that edges. - -There are functions that are unstable, but also provide value to coverage, eg -init functions that use fuzz data as input for example. -If however a function that has nothing to do with the input data is the -source of instability, e.g. checking jitter, or is a hash map function etc. -then it should not be instrumented. - -To be able to exclude these functions (based on AFL++'s measured stability) -the following process will allow to identify functions with variable edges. - -Four steps are required to do this and it also requires quite some knowledge -of coding and/or disassembly and is effectively possible only with -afl-clang-fast PCGUARD and afl-clang-lto LTO instrumentation. - - 1. First step: Instrument to be able to find the responsible function(s). - - a) For LTO instrumented binaries this can be documented during compile - time, just set `export AFL_LLVM_DOCUMENT_IDS=/path/to/a/file`. - This file will have one assigned edge ID and the corresponding - function per line. - - b) For PCGUARD instrumented binaries it is much more difficult. Here you - can either modify the __sanitizer_cov_trace_pc_guard function in - instrumentation/afl-llvm-rt.o.c to write a backtrace to a file if the ID in - __afl_area_ptr[*guard] is one of the unstable edge IDs. - (Example code is already there). - Then recompile and reinstall llvm_mode and rebuild your target. - Run the recompiled target with afl-fuzz for a while and then check the - file that you wrote with the backtrace information. - Alternatively you can use `gdb` to hook __sanitizer_cov_trace_pc_guard_init - on start, check to which memory address the edge ID value is written - and set a write breakpoint to that address (`watch 0x.....`). - - c) in all other instrumentation types this is not possible. So just - recompile with the two mentioned above. This is just for - identifying the functions that have unstable edges. - - 2. Second step: Identify which edge ID numbers are unstable - - run the target with `export AFL_DEBUG=1` for a few minutes then terminate. - The out/fuzzer_stats file will then show the edge IDs that were identified - as unstable in the `var_bytes` entry. You can match these numbers - directly to the data you created in the first step. - Now you know which functions are responsible for the instability - - 3. Third step: create a text file with the filenames/functions - - Identify which source code files contain the functions that you need to - remove from instrumentation, or just specify the functions you want to - skip for instrumentation. Note that optimization might inline functions! - - Simply follow this document on how to do this: [instrumentation/README.instrument_list.md](../instrumentation/README.instrument_list.md) - If PCGUARD is used, then you need to follow this guide (needs llvm 12+!): - [http://clang.llvm.org/docs/SanitizerCoverage.html#partially-disabling-instrumentation](http://clang.llvm.org/docs/SanitizerCoverage.html#partially-disabling-instrumentation) - - Only exclude those functions from instrumentation that provide no value - for coverage - that is if it does not process any fuzz data directly - or indirectly (e.g. hash maps, thread management etc.). - If however a function directly or indirectly handles fuzz data then you - should not put the function in a deny instrumentation list and rather - live with the instability it comes with. - - 4. Fourth step: recompile the target - - Recompile, fuzz it, be happy :) - - This link explains this process for [Fuzzbench](https://github.com/google/fuzzbench/issues/677) + Block E + ``` + + Every line between two blocks is an `edge`. Note that a few basic block loop + to itself, this too would be an edge. +</p></details> + +## Targets + +<details> + <summary id="how-can-i-fuzz-a-binary-only-target">How can I fuzz a binary-only target?</summary><p> + + AFL++ is a great fuzzer if you have the source code available. + + However, if there is only the binary program and no source code available, + then the standard non-instrumented mode is not effective. + + To learn how these binaries can be fuzzed, read + [fuzzing_binary-only_targets.md](fuzzing_binary-only_targets.md). +</p></details> + +<details> + <summary id="how-can-i-fuzz-a-network-service">How can I fuzz a network service?</summary><p> + + The short answer is - you cannot, at least not "out of the box". + + For more information on fuzzing network services, see + [best_practices.md#fuzzing-a-network-service](best_practices.md#fuzzing-a-network-service). +</p></details> + +<details> + <summary id="how-can-i-fuzz-a-gui-program">How can I fuzz a GUI program?</summary><p> + + Not all GUI programs are suitable for fuzzing. If the GUI program can read the + fuzz data from a file without needing any user interaction, then it would be + suitable for fuzzing. + + For more information on fuzzing GUI programs, see + [best_practices.md#fuzzing-a-gui-program](best_practices.md#fuzzing-a-gui-program). +</p></details> + +## Performance + +<details> + <summary id="how-can-i-improve-the-fuzzing-speed">How can I improve the fuzzing speed?</summary><p> + + There are a few things you can do to improve the fuzzing speed, see + [best_practices.md#improving-speed](best_practices.md#improving-speed). +</p></details> + +<details> + <summary id="why-is-my-stability-below-100percent">Why is my stability below 100%?</summary><p> + + Stability is measured by how many percent of the edges in the target are + "stable". Sending the same input again and again should take the exact same + path through the target every time. If that is the case, the stability is + 100%. + + If, however, randomness happens, e.g., a thread reading other external data, + reaction to timing, etc., then in some of the re-executions with the same data + the edge coverage result will be different across runs. Those edges that + change are then flagged "unstable". + + The more "unstable" edges, the more difficult for AFL++ to identify valid new + paths. + + A value above 90% is usually fine and a value above 80% is also still ok, and + even a value above 20% can still result in successful finds of bugs. However, + it is recommended that for values below 90% or 80% you should take + countermeasures to improve stability. + + For more information on stability and how to improve the stability value, see + [best_practices.md#improving-stability](best_practices.md#improving-stability). +</p></details> + +## Troubleshooting + +<details> + <summary id="i-got-a-weird-compile-error-from-clang">I got a weird compile error from clang.</summary><p> + + If you see this kind of error when trying to instrument a target with + afl-cc/afl-clang-fast/afl-clang-lto: + + ``` + /prg/tmp/llvm-project/build/bin/clang-13: symbol lookup error: /usr/local/bin/../lib/afl//cmplog-instructions-pass.so: undefined symbol: _ZNK4llvm8TypeSizecvmEv + clang-13: error: unable to execute command: No such file or directory + clang-13: error: clang frontend command failed due to signal (use -v to see invocation) + clang version 13.0.0 (https://github.com/llvm/llvm-project 1d7cf550721c51030144f3cd295c5789d51c4aad) + Target: x86_64-unknown-linux-gnu + Thread model: posix + InstalledDir: /prg/tmp/llvm-project/build/bin + clang-13: note: diagnostic msg: + ******************** + ``` + + Then this means that your OS updated the clang installation from an upgrade + package and because of that the AFL++ llvm plugins do not match anymore. + + Solution: `git pull ; make clean install` of AFL++. +</p></details> \ No newline at end of file diff --git a/docs/INSTALL.md b/docs/INSTALL.md index 17af532a..906d3f8e 100644 --- a/docs/INSTALL.md +++ b/docs/INSTALL.md @@ -1,82 +1,101 @@ -# Installation instructions +# Building and installing AFL++ - This document provides basic installation instructions and discusses known - issues for a variety of platforms. See README.md for the general instruction - manual. +## Linux on x86 -## 1. Linux on x86 ---------------- +An easy way to install AFL++ with everything compiled is available via docker: +You can use the [Dockerfile](../Dockerfile) (which has gcc-10 and clang-11 - +hence afl-clang-lto is available!) or just pull directly from the Docker Hub: -This platform is expected to work well. Compile the program with: - -```bash -make +```shell +docker pull aflplusplus/aflplusplus +docker run -ti -v /location/of/your/target:/src aflplusplus/aflplusplus ``` -You can start using the fuzzer without installation, but it is also possible to -install it with: - -```bash +This image is automatically generated when a push to the stable repo happens. +You will find your target source code in /src in the container. + +If you want to build AFL++ yourself, you have many options. The easiest choice +is to build and install everything: + +```shell +sudo apt-get update +sudo apt-get install -y build-essential python3-dev automake git flex bison libglib2.0-dev libpixman-1-dev python3-setuptools +# try to install llvm 11 and install the distro default if that fails +sudo apt-get install -y lld-11 llvm-11 llvm-11-dev clang-11 || sudo apt-get install -y lld llvm llvm-dev clang +sudo apt-get install -y gcc-$(gcc --version|head -n1|sed 's/.* //'|sed 's/\..*//')-plugin-dev libstdc++-$(gcc --version|head -n1|sed 's/.* //'|sed 's/\..*//')-dev +sudo apt-get install -y ninja-build # for QEMU mode +git clone https://github.com/AFLplusplus/AFLplusplus +cd AFLplusplus +make distrib sudo make install ``` -There are no special dependencies to speak of; you will need GNU make and a -working compiler (gcc or clang). Some of the optional scripts bundled with the -program may depend on bash, gdb, and similar basic tools. - -If you are using clang, please review README.llvm.md; the LLVM -integration mode can offer substantial performance gains compared to the -traditional approach. +It is recommended to install the newest available gcc, clang and llvm-dev +possible in your distribution! -Likewise, if you are using GCC, please review instrumentation/README.gcc_plugin.md. +Note that "make distrib" also builds instrumentation, QEMU mode, unicorn_mode +and more. If you just want plain AFL++, then do "make all". However, compiling +and using at least instrumentation is highly recommended for much better results +- hence in this case choose: -You may have to change several settings to get optimal results (most notably, -disable crash reporting utilities and switch to a different CPU governor), but -afl-fuzz will guide you through that if necessary. - -## 2. OpenBSD, FreeBSD, NetBSD on x86 - -Similarly to Linux, these platforms are expected to work well and are -regularly tested. Compile everything with GNU make: - -```bash -gmake +```shell +make source-only ``` -Note that BSD make will *not* work; if you do not have gmake on your system, -please install it first. As on Linux, you can use the fuzzer itself without -installation, or install it with: - -``` -sudo gmake install +These build targets exist: + +* all: just the main AFL++ binaries +* binary-only: everything for binary-only fuzzing: qemu_mode, unicorn_mode, + libdislocator, libtokencap +* source-only: everything for source code fuzzing: instrumentation, + libdislocator, libtokencap +* distrib: everything (for both binary-only and source code fuzzing) +* man: creates simple man pages from the help option of the programs +* install: installs everything you have compiled with the build options above +* clean: cleans everything compiled, not downloads (unless not on a checkout) +* deepclean: cleans everything including downloads +* code-format: format the code, do this before you commit and send a PR please! +* tests: runs test cases to ensure that all features are still working as they + should +* unit: perform unit tests (based on cmocka) +* help: shows these build options + +[Unless you are on Mac OS X](https://developer.apple.com/library/archive/qa/qa1118/_index.html), +you can also build statically linked versions of the AFL++ binaries by passing +the `STATIC=1` argument to make: + +```shell +make STATIC=1 ``` -Keep in mind that if you are using csh as your shell, the syntax of some of the -shell commands given in the README.md and other docs will be different. - -The `llvm` requires a dynamically linked, fully-operational installation of -clang. At least on FreeBSD, the clang binaries are static and do not include -some of the essential tools, so if you want to make it work, you may need to -follow the instructions in README.llvm.md. +These build options exist: -Beyond that, everything should work as advertised. +* STATIC - compile AFL++ static +* ASAN_BUILD - compiles with memory sanitizer for debug purposes +* DEBUG - no optimization, -ggdb3, all warnings and -Werror +* PROFILING - compile with profiling information (gprof) +* INTROSPECTION - compile afl-fuzz with mutation introspection +* NO_PYTHON - disable python support +* NO_SPLICING - disables splicing mutation in afl-fuzz, not recommended for + normal fuzzing +* AFL_NO_X86 - if compiling on non-intel/amd platforms +* LLVM_CONFIG - if your distro doesn't use the standard name for llvm-config + (e.g., Debian) -The QEMU mode is currently supported only on Linux. I think it's just a QEMU -problem, I couldn't get a vanilla copy of user-mode emulation support working -correctly on BSD at all. +e.g.: `make ASAN_BUILD=1` -## 3. MacOS X on x86 and arm64 (M1) +## MacOS X on x86 and arm64 (M1) -MacOS X should work, but there are some gotchas due to the idiosyncrasies of -the platform. On top of this, I have limited release testing capabilities -and depend mostly on user feedback. +MacOS X should work, but there are some gotchas due to the idiosyncrasies of the +platform. On top of this, we have limited release testing capabilities and +depend mostly on user feedback. To build AFL, install llvm (and perhaps gcc) from brew and follow the general -instructions for Linux. If possible avoid Xcode at all cost. +instructions for Linux. If possible, avoid Xcode at all cost. `brew install wget git make cmake llvm gdb` -Be sure to setup PATH to point to the correct clang binaries and use the +Be sure to setup `PATH` to point to the correct clang binaries and use the freshly installed clang, clang++ and gmake, e.g.: ``` @@ -90,12 +109,13 @@ cd .. gmake install ``` -afl-gcc will fail unless you have GCC installed, but that is using outdated -instrumentation anyway. You don't want that. -Note that afl-clang-lto, afl-gcc-fast and qemu_mode are not working on MacOS. +`afl-gcc` will fail unless you have GCC installed, but that is using outdated +instrumentation anyway. You don't want that. Note that `afl-clang-lto`, +`afl-gcc-fast` and `qemu_mode` are not working on MacOS. The crash reporting daemon that comes by default with MacOS X will cause problems with fuzzing. You need to turn it off: + ``` launchctl unload -w /System/Library/LaunchAgents/com.apple.ReportCrash.plist sudo launchctl unload -w /System/Library/LaunchDaemons/com.apple.ReportCrash.Root.plist @@ -107,17 +127,17 @@ and definitely don't look POSIX-compliant. This means two things: - Fuzzing will be probably slower than on Linux. In fact, some folks report considerable performance gains by running the jobs inside a Linux VM on MacOS X. - - Some non-portable, platform-specific code may be incompatible with the - AFL forkserver. If you run into any problems, set `AFL_NO_FORKSRV=1` in the + - Some non-portable, platform-specific code may be incompatible with the AFL++ + forkserver. If you run into any problems, set `AFL_NO_FORKSRV=1` in the environment before starting afl-fuzz. User emulation mode of QEMU does not appear to be supported on MacOS X, so -black-box instrumentation mode (`-Q`) will not work. -However Frida mode (`-O`) should work on x86 and arm64 MacOS boxes. +black-box instrumentation mode (`-Q`) will not work. However, Frida mode (`-O`) +should work on x86 and arm64 MacOS boxes. MacOS X supports SYSV shared memory used by AFL's instrumentation, but the -default settings aren't usable with AFL++. The default settings on 10.14 seem -to be: +default settings aren't usable with AFL++. The default settings on 10.14 seem to +be: ```bash $ ipcs -M @@ -138,8 +158,8 @@ sysctl kern.sysv.shmmax=8388608 sysctl kern.sysv.shmall=4096 ``` -If you're running more than one instance of AFL you likely want to make `shmall` -bigger and increase `shmseg` as well: +If you're running more than one instance of AFL, you likely want to make +`shmall` bigger and increase `shmseg` as well: ```bash sysctl kern.sysv.shmmax=8388608 @@ -147,91 +167,6 @@ sysctl kern.sysv.shmseg=48 sysctl kern.sysv.shmall=98304 ``` -See http://www.spy-hill.com/help/apple/SharedMemory.html for documentation for -these settings and how to make them permanent. - -## 4. Linux or *BSD on non-x86 systems - -Standard build will fail on non-x86 systems, but you should be able to -leverage two other options: - - - The LLVM mode (see README.llvm.md), which does not rely on - x86-specific assembly shims. It's fast and robust, but requires a - complete installation of clang. - - The QEMU mode (see qemu_mode/README.md), which can be also used for - fuzzing cross-platform binaries. It's slower and more fragile, but - can be used even when you don't have the source for the tested app. - -If you're not sure what you need, you need the LLVM mode, which is built by -default. - -...and compile your target program with afl-clang-fast or afl-clang-fast++ -instead of the traditional afl-gcc or afl-clang wrappers. - -## 5. Solaris on x86 - -The fuzzer reportedly works on Solaris, but I have not tested this first-hand, -and the user base is fairly small, so I don't have a lot of feedback. - -To get the ball rolling, you will need to use GNU make and GCC or clang. I'm -being told that the stock version of GCC that comes with the platform does not -work properly due to its reliance on a hardcoded location for 'as' (completely -ignoring the `-B` parameter or `$PATH`). - -To fix this, you may want to build stock GCC from the source, like so: - -```sh -./configure --prefix=$HOME/gcc --with-gnu-as --with-gnu-ld \ - --with-gmp-include=/usr/include/gmp --with-mpfr-include=/usr/include/mpfr -make -sudo make install -``` - -Do *not* specify `--with-as=/usr/gnu/bin/as` - this will produce a GCC binary that -ignores the `-B` flag and you will be back to square one. - -Note that Solaris reportedly comes with crash reporting enabled, which causes -problems with crashes being misinterpreted as hangs, similarly to the gotchas -for Linux and MacOS X. AFL does not auto-detect crash reporting on this -particular platform, but you may need to run the following command: - -```sh -coreadm -d global -d global-setid -d process -d proc-setid \ - -d kzone -d log -``` - -User emulation mode of QEMU is not available on Solaris, so black-box -instrumentation mode (`-Q`) will not work. - -## 6. Everything else - -You're on your own. On POSIX-compliant systems, you may be able to compile and -run the fuzzer; and the LLVM and GCC plugin modes may offer a way to instrument -non-x86 code. - -The fuzzer will run on Windows in WSL only. It will not work under Cygwin on in the normal Windows world. It -could be ported to the latter platform fairly easily, but it's a pretty bad -idea, because Cygwin is extremely slow. It makes much more sense to use -VirtualBox or so to run a hardware-accelerated Linux VM; it will run around -20x faster or so. If you have a *really* compelling use case for Cygwin, let -me know. - -Although Android on x86 should theoretically work, the stock kernel may have -SHM support compiled out, and if so, you may have to address that issue first. -It's possible that all you need is this workaround: - - https://github.com/pelya/android-shmem - -Joshua J. Drake notes that the Android linker adds a shim that automatically -intercepts `SIGSEGV` and related signals. To fix this issue and be able to see -crashes, you need to put this at the beginning of the fuzzed program: - -```sh - signal(SIGILL, SIG_DFL); - signal(SIGABRT, SIG_DFL); - signal(SIGBUS, SIG_DFL); - signal(SIGFPE, SIG_DFL); - signal(SIGSEGV, SIG_DFL); -``` - -You may need to `#include <signal.h>` first. +See +[http://www.spy-hill.com/help/apple/SharedMemory.html](http://www.spy-hill.com/help/apple/SharedMemory.html) +for documentation for these settings and how to make them permanent. \ No newline at end of file diff --git a/docs/QuickStartGuide.md b/docs/QuickStartGuide.md deleted file mode 100644 index 2d056ecf..00000000 --- a/docs/QuickStartGuide.md +++ /dev/null @@ -1,50 +0,0 @@ -# AFL quick start guide - -You should read [README.md](../README.md) - it's pretty short. If you really can't, here's -how to hit the ground running: - -1) Compile AFL with 'make'. If build fails, see [INSTALL.md](INSTALL.md) for tips. - -2) Find or write a reasonably fast and simple program that takes data from - a file or stdin, processes it in a test-worthy way, then exits cleanly. - If testing a network service, modify it to run in the foreground and read - from stdin. When fuzzing a format that uses checksums, comment out the - checksum verification code, too. - - If this is not possible (e.g. in -Q(emu) mode) then use - AFL_CUSTOM_MUTATOR_LIBRARY to calculate the values with your own library. - - The program must crash properly when a fault is encountered. Watch out for - custom SIGSEGV or SIGABRT handlers and background processes. For tips on - detecting non-crashing flaws, see section 11 in [README.md](README.md) . - -3) Compile the program / library to be fuzzed using afl-cc. A common way to - do this would be: - - CC=/path/to/afl-cc CXX=/path/to/afl-c++ ./configure --disable-shared - make clean all - -4) Get a small but valid input file that makes sense to the program. When - fuzzing verbose syntax (SQL, HTTP, etc), create a dictionary as described in - dictionaries/README.md, too. - -5) If the program reads from stdin, run 'afl-fuzz' like so: - - ./afl-fuzz -i testcase_dir -o findings_dir -- \ - /path/to/tested/program [...program's cmdline...] - - If the program takes input from a file, you can put @@ in the program's - command line; AFL will put an auto-generated file name in there for you. - -6) Investigate anything shown in red in the fuzzer UI by promptly consulting - [status_screen.md](status_screen.md). - -8) There is a basic docker build with 'docker build -t aflplusplus .' - -That's it. Sit back, relax, and - time permitting - try to skim through the -following files: - - - README.md - A general introduction to AFL, - - docs/perf_tips.md - Simple tips on how to fuzz more quickly, - - docs/status_screen.md - An explanation of the tidbits shown in the UI, - - docs/parallel_fuzzing.md - Advice on running AFL on multiple cores. diff --git a/docs/afl-fuzz_approach.md b/docs/afl-fuzz_approach.md new file mode 100644 index 00000000..2da61cc4 --- /dev/null +++ b/docs/afl-fuzz_approach.md @@ -0,0 +1,543 @@ +# The afl-fuzz approach + +AFL++ is a brute-force fuzzer coupled with an exceedingly simple but rock-solid +instrumentation-guided genetic algorithm. It uses a modified form of edge +coverage to effortlessly pick up subtle, local-scale changes to program control +flow. + +Simplifying a bit, the overall algorithm can be summed up as: + +1) Load user-supplied initial test cases into the queue. + +2) Take the next input file from the queue. + +3) Attempt to trim the test case to the smallest size that doesn't alter the + measured behavior of the program. + +4) Repeatedly mutate the file using a balanced and well-researched variety of + traditional fuzzing strategies. + +5) If any of the generated mutations resulted in a new state transition recorded + by the instrumentation, add mutated output as a new entry in the queue. + +6) Go to 2. + +The discovered test cases are also periodically culled to eliminate ones that +have been obsoleted by newer, higher-coverage finds; and undergo several other +instrumentation-driven effort minimization steps. + +As a side result of the fuzzing process, the tool creates a small, +self-contained corpus of interesting test cases. These are extremely useful for +seeding other, labor- or resource-intensive testing regimes - for example, for +stress-testing browsers, office applications, graphics suites, or closed-source +tools. + +The fuzzer is thoroughly tested to deliver out-of-the-box performance far +superior to blind fuzzing or coverage-only tools. + +## Understanding the status screen + +This section provides an overview of the status screen - plus tips for +troubleshooting any warnings and red text shown in the UI. + +For the general instruction manual, see [README.md](../README.md). + +### A note about colors + +The status screen and error messages use colors to keep things readable and +attract your attention to the most important details. For example, red almost +always means "consult this doc" :-) + +Unfortunately, the UI will only render correctly if your terminal is using +traditional un*x palette (white text on black background) or something close to +that. + +If you are using inverse video, you may want to change your settings, say: + +- For GNOME Terminal, go to `Edit > Profile` preferences, select the "colors" + tab, and from the list of built-in schemes, choose "white on black". +- For the MacOS X Terminal app, open a new window using the "Pro" scheme via the + `Shell > New Window` menu (or make "Pro" your default). + +Alternatively, if you really like your current colors, you can edit config.h to +comment out USE_COLORS, then do `make clean all`. + +We are not aware of any other simple way to make this work without causing other +side effects - sorry about that. + +With that out of the way, let's talk about what's actually on the screen... + +### The status bar + +``` +american fuzzy lop ++3.01a (default) [fast] {0} +``` + +The top line shows you which mode afl-fuzz is running in (normal: "american +fuzzy lop", crash exploration mode: "peruvian rabbit mode") and the version of +AFL++. Next to the version is the banner, which, if not set with -T by hand, +will either show the binary name being fuzzed, or the -M/-S main/secondary name +for parallel fuzzing. Second to last is the power schedule mode being run +(default: fast). Finally, the last item is the CPU id. + +### Process timing + +``` + +----------------------------------------------------+ + | run time : 0 days, 8 hrs, 32 min, 43 sec | + | last new path : 0 days, 0 hrs, 6 min, 40 sec | + | last uniq crash : none seen yet | + | last uniq hang : 0 days, 1 hrs, 24 min, 32 sec | + +----------------------------------------------------+ +``` + +This section is fairly self-explanatory: it tells you how long the fuzzer has +been running and how much time has elapsed since its most recent finds. This is +broken down into "paths" (a shorthand for test cases that trigger new execution +patterns), crashes, and hangs. + +When it comes to timing: there is no hard rule, but most fuzzing jobs should be +expected to run for days or weeks; in fact, for a moderately complex project, +the first pass will probably take a day or so. Every now and then, some jobs +will be allowed to run for months. + +There's one important thing to watch out for: if the tool is not finding new +paths within several minutes of starting, you're probably not invoking the +target binary correctly and it never gets to parse the input files that are +thrown at it; other possible explanations are that the default memory limit +(`-m`) is too restrictive and the program exits after failing to allocate a +buffer very early on; or that the input files are patently invalid and always +fail a basic header check. + +If there are no new paths showing up for a while, you will eventually see a big +red warning in this section, too :-) + +### Overall results + +``` + +-----------------------+ + | cycles done : 0 | + | total paths : 2095 | + | uniq crashes : 0 | + | uniq hangs : 19 | + +-----------------------+ +``` + +The first field in this section gives you the count of queue passes done so far +- that is, the number of times the fuzzer went over all the interesting test + cases discovered so far, fuzzed them, and looped back to the very beginning. + Every fuzzing session should be allowed to complete at least one cycle; and + ideally, should run much longer than that. + +As noted earlier, the first pass can take a day or longer, so sit back and +relax. + +To help make the call on when to hit `Ctrl-C`, the cycle counter is color-coded. +It is shown in magenta during the first pass, progresses to yellow if new finds +are still being made in subsequent rounds, then blue when that ends - and +finally, turns green after the fuzzer hasn't been seeing any action for a longer +while. + +The remaining fields in this part of the screen should be pretty obvious: +there's the number of test cases ("paths") discovered so far, and the number of +unique faults. The test cases, crashes, and hangs can be explored in real-time +by browsing the output directory, see +[#interpreting-output](#interpreting-output). + +### Cycle progress + +``` + +-------------------------------------+ + | now processing : 1296 (61.86%) | + | paths timed out : 0 (0.00%) | + +-------------------------------------+ +``` + +This box tells you how far along the fuzzer is with the current queue cycle: it +shows the ID of the test case it is currently working on, plus the number of +inputs it decided to ditch because they were persistently timing out. + +The "*" suffix sometimes shown in the first line means that the currently +processed path is not "favored" (a property discussed later on). + +### Map coverage + +``` + +--------------------------------------+ + | map density : 10.15% / 29.07% | + | count coverage : 4.03 bits/tuple | + +--------------------------------------+ +``` + +The section provides some trivia about the coverage observed by the +instrumentation embedded in the target binary. + +The first line in the box tells you how many branch tuples already were hit, in +proportion to how much the bitmap can hold. The number on the left describes the +current input; the one on the right is the value for the entire input corpus. + +Be wary of extremes: + +- Absolute numbers below 200 or so suggest one of three things: that the program + is extremely simple; that it is not instrumented properly (e.g., due to being + linked against a non-instrumented copy of the target library); or that it is + bailing out prematurely on your input test cases. The fuzzer will try to mark + this in pink, just to make you aware. +- Percentages over 70% may very rarely happen with very complex programs that + make heavy use of template-generated code. Because high bitmap density makes + it harder for the fuzzer to reliably discern new program states, we recommend + recompiling the binary with `AFL_INST_RATIO=10` or so and trying again (see + [env_variables.md](env_variables.md)). The fuzzer will flag high percentages + in red. Chances are, you will never see that unless you're fuzzing extremely + hairy software (say, v8, perl, ffmpeg). + +The other line deals with the variability in tuple hit counts seen in the +binary. In essence, if every taken branch is always taken a fixed number of +times for all the inputs that were tried, this will read `1.00`. As we manage to +trigger other hit counts for every branch, the needle will start to move toward +`8.00` (every bit in the 8-bit map hit), but will probably never reach that +extreme. + +Together, the values can be useful for comparing the coverage of several +different fuzzing jobs that rely on the same instrumented binary. + +### Stage progress + +``` + +-------------------------------------+ + | now trying : interest 32/8 | + | stage execs : 3996/34.4k (11.62%) | + | total execs : 27.4M | + | exec speed : 891.7/sec | + +-------------------------------------+ +``` + +This part gives you an in-depth peek at what the fuzzer is actually doing right +now. It tells you about the current stage, which can be any of: + +- calibration - a pre-fuzzing stage where the execution path is examined to + detect anomalies, establish baseline execution speed, and so on. Executed very + briefly whenever a new find is being made. +- trim L/S - another pre-fuzzing stage where the test case is trimmed to the + shortest form that still produces the same execution path. The length (L) and + stepover (S) are chosen in general relationship to file size. +- bitflip L/S - deterministic bit flips. There are L bits toggled at any given + time, walking the input file with S-bit increments. The current L/S variants + are: `1/1`, `2/1`, `4/1`, `8/8`, `16/8`, `32/8`. +- arith L/8 - deterministic arithmetics. The fuzzer tries to subtract or add + small integers to 8-, 16-, and 32-bit values. The stepover is always 8 bits. +- interest L/8 - deterministic value overwrite. The fuzzer has a list of known + "interesting" 8-, 16-, and 32-bit values to try. The stepover is 8 bits. +- extras - deterministic injection of dictionary terms. This can be shown as + "user" or "auto", depending on whether the fuzzer is using a user-supplied + dictionary (`-x`) or an auto-created one. You will also see "over" or + "insert", depending on whether the dictionary words overwrite existing data or + are inserted by offsetting the remaining data to accommodate their length. +- havoc - a sort-of-fixed-length cycle with stacked random tweaks. The + operations attempted during this stage include bit flips, overwrites with + random and "interesting" integers, block deletion, block duplication, plus + assorted dictionary-related operations (if a dictionary is supplied in the + first place). +- splice - a last-resort strategy that kicks in after the first full queue cycle + with no new paths. It is equivalent to 'havoc', except that it first splices + together two random inputs from the queue at some arbitrarily selected + midpoint. +- sync - a stage used only when `-M` or `-S` is set (see + [fuzzing_in_depth.md:3c) Using multiple cores](fuzzing_in_depth.md#c-using-multiple-cores)). + No real fuzzing is involved, but the tool scans the output from other fuzzers + and imports test cases as necessary. The first time this is done, it may take + several minutes or so. + +The remaining fields should be fairly self-evident: there's the exec count +progress indicator for the current stage, a global exec counter, and a benchmark +for the current program execution speed. This may fluctuate from one test case +to another, but the benchmark should be ideally over 500 execs/sec most of the +time - and if it stays below 100, the job will probably take very long. + +The fuzzer will explicitly warn you about slow targets, too. If this happens, +see the [best_practices.md#improving-speed](best_practices.md#improving-speed) +for ideas on how to speed things up. + +### Findings in depth + +``` + +--------------------------------------+ + | favored paths : 879 (41.96%) | + | new edges on : 423 (20.19%) | + | total crashes : 0 (0 unique) | + | total tmouts : 24 (19 unique) | + +--------------------------------------+ +``` + +This gives you several metrics that are of interest mostly to complete nerds. +The section includes the number of paths that the fuzzer likes the most based on +a minimization algorithm baked into the code (these will get considerably more +air time), and the number of test cases that actually resulted in better edge +coverage (versus just pushing the branch hit counters up). There are also +additional, more detailed counters for crashes and timeouts. + +Note that the timeout counter is somewhat different from the hang counter; this +one includes all test cases that exceeded the timeout, even if they did not +exceed it by a margin sufficient to be classified as hangs. + +### Fuzzing strategy yields + +``` + +-----------------------------------------------------+ + | bit flips : 57/289k, 18/289k, 18/288k | + | byte flips : 0/36.2k, 4/35.7k, 7/34.6k | + | arithmetics : 53/2.54M, 0/537k, 0/55.2k | + | known ints : 8/322k, 12/1.32M, 10/1.70M | + | dictionary : 9/52k, 1/53k, 1/24k | + |havoc/splice : 1903/20.0M, 0/0 | + |py/custom/rq : unused, 53/2.54M, unused | + | trim/eff : 20.31%/9201, 17.05% | + +-----------------------------------------------------+ +``` + +This is just another nerd-targeted section keeping track of how many paths were +netted, in proportion to the number of execs attempted, for each of the fuzzing +strategies discussed earlier on. This serves to convincingly validate +assumptions about the usefulness of the various approaches taken by afl-fuzz. + +The trim strategy stats in this section are a bit different than the rest. The +first number in this line shows the ratio of bytes removed from the input files; +the second one corresponds to the number of execs needed to achieve this goal. +Finally, the third number shows the proportion of bytes that, although not +possible to remove, were deemed to have no effect and were excluded from some of +the more expensive deterministic fuzzing steps. + +Note that when deterministic mutation mode is off (which is the default because +it is not very efficient) the first five lines display "disabled (default, +enable with -D)". + +Only what is activated will have counter shown. + +### Path geometry + +``` + +---------------------+ + | levels : 5 | + | pending : 1570 | + | pend fav : 583 | + | own finds : 0 | + | imported : 0 | + | stability : 100.00% | + +---------------------+ +``` + +The first field in this section tracks the path depth reached through the guided +fuzzing process. In essence: the initial test cases supplied by the user are +considered "level 1". The test cases that can be derived from that through +traditional fuzzing are considered "level 2"; the ones derived by using these as +inputs to subsequent fuzzing rounds are "level 3"; and so forth. The maximum +depth is therefore a rough proxy for how much value you're getting out of the +instrumentation-guided approach taken by afl-fuzz. + +The next field shows you the number of inputs that have not gone through any +fuzzing yet. The same stat is also given for "favored" entries that the fuzzer +really wants to get to in this queue cycle (the non-favored entries may have to +wait a couple of cycles to get their chance). + +Next is the number of new paths found during this fuzzing section and imported +from other fuzzer instances when doing parallelized fuzzing; and the extent to +which identical inputs appear to sometimes produce variable behavior in the +tested binary. + +That last bit is actually fairly interesting: it measures the consistency of +observed traces. If a program always behaves the same for the same input data, +it will earn a score of 100%. When the value is lower but still shown in purple, +the fuzzing process is unlikely to be negatively affected. If it goes into red, +you may be in trouble, since AFL++ will have difficulty discerning between +meaningful and "phantom" effects of tweaking the input file. + +Now, most targets will just get a 100% score, but when you see lower figures, +there are several things to look at: + +- The use of uninitialized memory in conjunction with some intrinsic sources of + entropy in the tested binary. Harmless to AFL, but could be indicative of a + security bug. +- Attempts to manipulate persistent resources, such as left over temporary files + or shared memory objects. This is usually harmless, but you may want to + double-check to make sure the program isn't bailing out prematurely. Running + out of disk space, SHM handles, or other global resources can trigger this, + too. +- Hitting some functionality that is actually designed to behave randomly. + Generally harmless. For example, when fuzzing sqlite, an input like `select + random();` will trigger a variable execution path. +- Multiple threads executing at once in semi-random order. This is harmless when + the 'stability' metric stays over 90% or so, but can become an issue if not. + Here's what to try: + * Use afl-clang-fast from [instrumentation](../instrumentation/) - it uses a + thread-local tracking model that is less prone to concurrency issues, + * See if the target can be compiled or run without threads. Common + `./configure` options include `--without-threads`, `--disable-pthreads`, or + `--disable-openmp`. + * Replace pthreads with GNU Pth (https://www.gnu.org/software/pth/), which + allows you to use a deterministic scheduler. +- In persistent mode, minor drops in the "stability" metric can be normal, + because not all the code behaves identically when re-entered; but major dips + may signify that the code within `__AFL_LOOP()` is not behaving correctly on + subsequent iterations (e.g., due to incomplete clean-up or reinitialization of + the state) and that most of the fuzzing effort goes to waste. + +The paths where variable behavior is detected are marked with a matching entry +in the `<out_dir>/queue/.state/variable_behavior/` directory, so you can look +them up easily. + +### CPU load + +``` + [cpu: 25%] +``` + +This tiny widget shows the apparent CPU utilization on the local system. It is +calculated by taking the number of processes in the "runnable" state, and then +comparing it to the number of logical cores on the system. + +If the value is shown in green, you are using fewer CPU cores than available on +your system and can probably parallelize to improve performance; for tips on how +to do that, see +[fuzzing_in_depth.md:3c) Using multiple cores](fuzzing_in_depth.md#c-using-multiple-cores). + +If the value is shown in red, your CPU is *possibly* oversubscribed, and running +additional fuzzers may not give you any benefits. + +Of course, this benchmark is very simplistic; it tells you how many processes +are ready to run, but not how resource-hungry they may be. It also doesn't +distinguish between physical cores, logical cores, and virtualized CPUs; the +performance characteristics of each of these will differ quite a bit. + +If you want a more accurate measurement, you can run the `afl-gotcpu` utility +from the command line. + +## Interpreting output + +See [#understanding-the-status-screen](#understanding-the-status-screen) for +information on how to interpret the displayed stats and monitor the health of +the process. Be sure to consult this file especially if any UI elements are +highlighted in red. + +The fuzzing process will continue until you press Ctrl-C. At a minimum, you want +to allow the fuzzer to complete one queue cycle, which may take anywhere from a +couple of hours to a week or so. + +There are three subdirectories created within the output directory and updated +in real-time: + +- queue/ - test cases for every distinctive execution path, plus all the + starting files given by the user. This is the synthesized corpus. + + Before using this corpus for any other purposes, you can shrink + it to a smaller size using the afl-cmin tool. The tool will find + a smaller subset of files offering equivalent edge coverage. + +- crashes/ - unique test cases that cause the tested program to receive a fatal + signal (e.g., SIGSEGV, SIGILL, SIGABRT). The entries are grouped by + the received signal. + +- hangs/ - unique test cases that cause the tested program to time out. The + default time limit before something is classified as a hang is the + larger of 1 second and the value of the -t parameter. The value can + be fine-tuned by setting AFL_HANG_TMOUT, but this is rarely + necessary. + +Crashes and hangs are considered "unique" if the associated execution paths +involve any state transitions not seen in previously-recorded faults. If a +single bug can be reached in multiple ways, there will be some count inflation +early in the process, but this should quickly taper off. + +The file names for crashes and hangs are correlated with the parent, +non-faulting queue entries. This should help with debugging. + +## Visualizing + +If you have gnuplot installed, you can also generate some pretty graphs for any +active fuzzing task using afl-plot. For an example of how this looks like, see +[https://lcamtuf.coredump.cx/afl/plot/](https://lcamtuf.coredump.cx/afl/plot/). + +You can also manually build and install afl-plot-ui, which is a helper utility +for showing the graphs generated by afl-plot in a graphical window using GTK. +You can build and install it as follows: + +```shell +sudo apt install libgtk-3-0 libgtk-3-dev pkg-config +cd utils/plot_ui +make +cd ../../ +sudo make install +``` + +To learn more about remote monitoring and metrics visualization with StatsD, see +[rpc_statsd.md](rpc_statsd.md). + +### Addendum: status and plot files + +For unattended operation, some of the key status screen information can be also +found in a machine-readable format in the fuzzer_stats file in the output +directory. This includes: + +- `start_time` - unix time indicating the start time of afl-fuzz +- `last_update` - unix time corresponding to the last update of this file +- `run_time` - run time in seconds to the last update of this file +- `fuzzer_pid` - PID of the fuzzer process +- `cycles_done` - queue cycles completed so far +- `cycles_wo_finds` - number of cycles without any new paths found +- `execs_done` - number of execve() calls attempted +- `execs_per_sec` - overall number of execs per second +- `paths_total` - total number of entries in the queue +- `paths_favored` - number of queue entries that are favored +- `paths_found` - number of entries discovered through local fuzzing +- `paths_imported` - number of entries imported from other instances +- `max_depth` - number of levels in the generated data set +- `cur_path` - currently processed entry number +- `pending_favs` - number of favored entries still waiting to be fuzzed +- `pending_total` - number of all entries waiting to be fuzzed +- `variable_paths` - number of test cases showing variable behavior +- `stability` - percentage of bitmap bytes that behave consistently +- `bitmap_cvg` - percentage of edge coverage found in the map so far +- `unique_crashes` - number of unique crashes recorded +- `unique_hangs` - number of unique hangs encountered +- `last_path` - seconds since the last path was found +- `last_crash` - seconds since the last crash was found +- `last_hang` - seconds since the last hang was found +- `execs_since_crash` - execs since the last crash was found +- `exec_timeout` - the -t command line value +- `slowest_exec_ms` - real time of the slowest execution in ms +- `peak_rss_mb` - max rss usage reached during fuzzing in MB +- `edges_found` - how many edges have been found +- `var_byte_count` - how many edges are non-deterministic +- `afl_banner` - banner text (e.g., the target name) +- `afl_version` - the version of AFL++ used +- `target_mode` - default, persistent, qemu, unicorn, non-instrumented +- `command_line` - full command line used for the fuzzing session + +Most of these map directly to the UI elements discussed earlier on. + +On top of that, you can also find an entry called `plot_data`, containing a +plottable history for most of these fields. If you have gnuplot installed, you +can turn this into a nice progress report with the included `afl-plot` tool. + +### Addendum: automatically sending metrics with StatsD + +In a CI environment or when running multiple fuzzers, it can be tedious to log +into each of them or deploy scripts to read the fuzzer statistics. Using +`AFL_STATSD` (and the other related environment variables `AFL_STATSD_HOST`, +`AFL_STATSD_PORT`, `AFL_STATSD_TAGS_FLAVOR`) you can automatically send metrics +to your favorite StatsD server. Depending on your StatsD server, you will be +able to monitor, trigger alerts, or perform actions based on these metrics +(e.g.: alert on slow exec/s for a new build, threshold of crashes, time since +last crash > X, etc.). + +The selected metrics are a subset of all the metrics found in the status and in +the plot file. The list is the following: `cycle_done`, `cycles_wo_finds`, +`execs_done`,`execs_per_sec`, `paths_total`, `paths_favored`, `paths_found`, +`paths_imported`, `max_depth`, `cur_path`, `pending_favs`, `pending_total`, +`variable_paths`, `unique_crashes`, `unique_hangs`, `total_crashes`, +`slowest_exec_ms`, `edges_found`, `var_byte_count`, `havoc_expansion`. Their +definitions can be found in the addendum above. + +When using multiple fuzzer instances with StatsD, it is *strongly* recommended +to setup the flavor (`AFL_STATSD_TAGS_FLAVOR`) to match your StatsD server. This +will allow you to see individual fuzzer performance, detect bad ones, see the +progress of each strategy... \ No newline at end of file diff --git a/docs/best_practices.md b/docs/best_practices.md new file mode 100644 index 00000000..96c6e3c2 --- /dev/null +++ b/docs/best_practices.md @@ -0,0 +1,192 @@ +# Best practices + +## Contents + +### Targets + +* [Fuzzing a target with source code available](#fuzzing-a-target-with-source-code-available) +* [Fuzzing a target with dlopen() instrumented libraries](#fuzzing-a-target-with-dlopen-instrumented-libraries) +* [Fuzzing a binary-only target](#fuzzing-a-binary-only-target) +* [Fuzzing a GUI program](#fuzzing-a-gui-program) +* [Fuzzing a network service](#fuzzing-a-network-service) + +### Improvements + +* [Improving speed](#improving-speed) +* [Improving stability](#improving-stability) + +## Targets + +### Fuzzing a target with source code available + +To learn how to fuzz a target if source code is available, see +[fuzzing_in_depth.md](fuzzing_in_depth.md). + +### Fuzzing a target with dlopen instrumented libraries + +If a source code based fuzzing target loads instrumented libraries with +dlopen() after the forkserver has been activated and non-colliding coverage +instrumentation is used (PCGUARD (which is the default), or LTO), then this +an issue, because this would enlarge the coverage map, but afl-fuzz doesn't +know about it. + +The solution is to use `AFL_PRELOAD` for all dlopen()'ed libraries to +ensure that all coverage targets are present on startup in the target, +even if accessed only later with dlopen(). + +For PCGUARD instrumentation `abort()` is called if this is detected, for LTO +there will either be no coverage for the instrumented dlopen()'ed libraries or +you will see lots of crashes in the UI. + +Note that this is not an issue if you use the inferiour `afl-gcc-fast`, +`afl-gcc` or`AFL_LLVM_INSTRUMENT=CLASSIC/NGRAM/CTX afl-clang-fast` +instrumentation. + +### Fuzzing a binary-only target + +For a comprehensive guide, see +[fuzzing_binary-only_targets.md](fuzzing_binary-only_targets.md). + +### Fuzzing a GUI program + +If the GUI program can read the fuzz data from a file (via the command line, a +fixed location or via an environment variable) without needing any user +interaction, then it would be suitable for fuzzing. + +Otherwise, it is not possible without modifying the source code - which is a +very good idea anyway as the GUI functionality is a huge CPU/time overhead for +the fuzzing. + +So create a new `main()` that just reads the test case and calls the +functionality for processing the input that the GUI program is using. + +### Fuzzing a network service + +Fuzzing a network service does not work "out of the box". + +Using a network channel is inadequate for several reasons: +- it has a slow-down of x10-20 on the fuzzing speed +- it does not scale to fuzzing multiple instances easily, +- instead of one initial data packet often a back-and-forth interplay of packets + is needed for stateful protocols (which is totally unsupported by most + coverage aware fuzzers). + +The established method to fuzz network services is to modify the source code to +read from a file or stdin (fd 0) (or even faster via shared memory, combine this +with persistent mode +[instrumentation/README.persistent_mode.md](../instrumentation/README.persistent_mode.md) +and you have a performance gain of x10 instead of a performance loss of over x10 +- that is a x100 difference!). + +If modifying the source is not an option (e.g., because you only have a binary +and perform binary fuzzing) you can also use a shared library with AFL_PRELOAD +to emulate the network. This is also much faster than the real network would be. +See [utils/socket_fuzzing/](../utils/socket_fuzzing/). + +There is an outdated AFL++ branch that implements networking if you are +desperate though: +[https://github.com/AFLplusplus/AFLplusplus/tree/networking](https://github.com/AFLplusplus/AFLplusplus/tree/networking) +- however, a better option is AFLnet +([https://github.com/aflnet/aflnet](https://github.com/aflnet/aflnet)) which +allows you to define network state with different type of data packets. + +## Improvements + +### Improving speed + +1. Use [llvm_mode](../instrumentation/README.llvm.md): afl-clang-lto (llvm >= + 11) or afl-clang-fast (llvm >= 9 recommended). +2. Use [persistent mode](../instrumentation/README.persistent_mode.md) (x2-x20 + speed increase). +3. Instrument just what you are interested in, see + [instrumentation/README.instrument_list.md](../instrumentation/README.instrument_list.md). +4. If you do not use shmem persistent mode, use `AFL_TMPDIR` to put the input + file directory on a tempfs location, see + [env_variables.md](env_variables.md). +5. Improve Linux kernel performance: modify `/etc/default/grub`, set + `GRUB_CMDLINE_LINUX_DEFAULT="ibpb=off ibrs=off kpti=off l1tf=off mds=off + mitigations=off no_stf_barrier noibpb noibrs nopcid nopti + nospec_store_bypass_disable nospectre_v1 nospectre_v2 pcid=off pti=off + spec_store_bypass_disable=off spectre_v2=off stf_barrier=off"`; then + `update-grub` and `reboot` (warning: makes the system less secure). +6. Running on an `ext2` filesystem with `noatime` mount option will be a bit + faster than on any other journaling filesystem. +7. Use your cores + ([fuzzing_in_depth.md:3c) Using multiple cores](fuzzing_in_depth.md#c-using-multiple-cores))! + +### Improving stability + +For fuzzing a 100% stable target that covers all edges is the best case. A 90% +stable target that covers all edges is, however, better than a 100% stable +target that ignores 10% of the edges. + +With instability, you basically have a partial coverage loss on an edge, with +ignored functions you have a full loss on that edges. + +There are functions that are unstable, but also provide value to coverage, e.g., +init functions that use fuzz data as input. If, however, a function that has +nothing to do with the input data is the source of instability, e.g., checking +jitter, or is a hash map function etc., then it should not be instrumented. + +To be able to exclude these functions (based on AFL++'s measured stability), the +following process will allow to identify functions with variable edges. + +Four steps are required to do this and it also requires quite some knowledge of +coding and/or disassembly and is effectively possible only with `afl-clang-fast` +`PCGUARD` and `afl-clang-lto` `LTO` instrumentation. + + 1. Instrument to be able to find the responsible function(s): + + a) For LTO instrumented binaries, this can be documented during compile + time, just set `export AFL_LLVM_DOCUMENT_IDS=/path/to/a/file`. This file + will have one assigned edge ID and the corresponding function per line. + + b) For PCGUARD instrumented binaries, it is much more difficult. Here you + can either modify the `__sanitizer_cov_trace_pc_guard` function in + `instrumentation/afl-llvm-rt.o.c` to write a backtrace to a file if the + ID in `__afl_area_ptr[*guard]` is one of the unstable edge IDs. (Example + code is already there). Then recompile and reinstall `llvm_mode` and + rebuild your target. Run the recompiled target with `afl-fuzz` for a + while and then check the file that you wrote with the backtrace + information. Alternatively, you can use `gdb` to hook + `__sanitizer_cov_trace_pc_guard_init` on start, check to which memory + address the edge ID value is written, and set a write breakpoint to that + address (`watch 0x.....`). + + c) In other instrumentation types, this is not possible. So just recompile + with the two mentioned above. This is just for identifying the functions + that have unstable edges. + + 2. Identify which edge ID numbers are unstable. + + Run the target with `export AFL_DEBUG=1` for a few minutes then terminate. + The out/fuzzer_stats file will then show the edge IDs that were identified + as unstable in the `var_bytes` entry. You can match these numbers directly + to the data you created in the first step. Now you know which functions are + responsible for the instability + + 3. Create a text file with the filenames/functions + + Identify which source code files contain the functions that you need to + remove from instrumentation, or just specify the functions you want to skip + for instrumentation. Note that optimization might inline functions! + + Follow this document on how to do this: + [instrumentation/README.instrument_list.md](../instrumentation/README.instrument_list.md). + + If `PCGUARD` is used, then you need to follow this guide (needs llvm 12+!): + [https://clang.llvm.org/docs/SanitizerCoverage.html#partially-disabling-instrumentation](https://clang.llvm.org/docs/SanitizerCoverage.html#partially-disabling-instrumentation) + + Only exclude those functions from instrumentation that provide no value for + coverage - that is if it does not process any fuzz data directly or + indirectly (e.g., hash maps, thread management etc.). If, however, a + function directly or indirectly handles fuzz data, then you should not put + the function in a deny instrumentation list and rather live with the + instability it comes with. + + 4. Recompile the target + + Recompile, fuzz it, be happy :) + + This link explains this process for + [Fuzzbench](https://github.com/google/fuzzbench/issues/677). \ No newline at end of file diff --git a/docs/binaryonly_fuzzing.md b/docs/binaryonly_fuzzing.md deleted file mode 100644 index 90ea3b66..00000000 --- a/docs/binaryonly_fuzzing.md +++ /dev/null @@ -1,223 +0,0 @@ -# Fuzzing binary-only programs with AFL++ - - AFL++, libfuzzer and others are great if you have the source code, and - it allows for very fast and coverage guided fuzzing. - - However, if there is only the binary program and no source code available, - then standard `afl-fuzz -n` (non-instrumented mode) is not effective. - - The following is a description of how these binaries can be fuzzed with AFL++. - - -## TL;DR: - - qemu_mode in persistent mode is the fastest - if the stability is - high enough. Otherwise try retrowrite, afl-dyninst and if these - fail too then try standard qemu_mode with AFL_ENTRYPOINT to where you need it. - - If your target is a library use utils/afl_frida/. - - If your target is non-linux then use unicorn_mode/. - - -## QEMU - - Qemu is the "native" solution to the program. - It is available in the ./qemu_mode/ directory and once compiled it can - be accessed by the afl-fuzz -Q command line option. - It is the easiest to use alternative and even works for cross-platform binaries. - - The speed decrease is at about 50%. - However various options exist to increase the speed: - - using AFL_ENTRYPOINT to move the forkserver entry to a later basic block in - the binary (+5-10% speed) - - using persistent mode [qemu_mode/README.persistent.md](../qemu_mode/README.persistent.md) - this will result in 150-300% overall speed increase - so 3-8x the original - qemu_mode speed! - - using AFL_CODE_START/AFL_CODE_END to only instrument specific parts - - Note that there is also honggfuzz: [https://github.com/google/honggfuzz](https://github.com/google/honggfuzz) - which now has a qemu_mode, but its performance is just 1.5% ... - - As it is included in AFL++ this needs no URL. - - If you like to code a customized fuzzer without much work, we highly - recommend to check out our sister project libafl which will support QEMU - too: - [https://github.com/AFLplusplus/LibAFL](https://github.com/AFLplusplus/LibAFL) - - -## AFL FRIDA - - In frida_mode you can fuzz binary-only targets easily like with QEMU, - with the advantage that frida_mode also works on MacOS (both intel and M1). - - If you want to fuzz a binary-only library then you can fuzz it with - frida-gum via utils/afl_frida/, you will have to write a harness to - call the target function in the library, use afl-frida.c as a template. - - Both come with AFL++ so this needs no URL. - - You can also perform remote fuzzing with frida, e.g. if you want to fuzz - on iPhone or Android devices, for this you can use - [https://github.com/ttdennis/fpicker/](https://github.com/ttdennis/fpicker/) - as an intermediate that uses AFL++ for fuzzing. - - If you like to code a customized fuzzer without much work, we highly - recommend to check out our sister project libafl which supports Frida too: - [https://github.com/AFLplusplus/LibAFL](https://github.com/AFLplusplus/LibAFL) - Working examples already exist :-) - - -## WINE+QEMU - - Wine mode can run Win32 PE binaries with the QEMU instrumentation. - It needs Wine, python3 and the pefile python package installed. - - As it is included in AFL++ this needs no URL. - - -## UNICORN - - Unicorn is a fork of QEMU. The instrumentation is, therefore, very similar. - In contrast to QEMU, Unicorn does not offer a full system or even userland - emulation. Runtime environment and/or loaders have to be written from scratch, - if needed. On top, block chaining has been removed. This means the speed boost - introduced in the patched QEMU Mode of AFL++ cannot simply be ported over to - Unicorn. For further information, check out [unicorn_mode/README.md](../unicorn_mode/README.md). - - As it is included in AFL++ this needs no URL. - - -## AFL UNTRACER - - If you want to fuzz a binary-only shared library then you can fuzz it with - utils/afl_untracer/, use afl-untracer.c as a template. - It is slower than AFL FRIDA (see above). - - -## DYNINST - - Dyninst is a binary instrumentation framework similar to Pintool and - Dynamorio (see far below). However whereas Pintool and Dynamorio work at - runtime, dyninst instruments the target at load time, and then let it run - - or save the binary with the changes. - This is great for some things, e.g. fuzzing, and not so effective for others, - e.g. malware analysis. - - So what we can do with dyninst is taking every basic block, and put afl's - instrumention code in there - and then save the binary. - Afterwards we can just fuzz the newly saved target binary with afl-fuzz. - Sounds great? It is. The issue though - it is a non-trivial problem to - insert instructions, which change addresses in the process space, so that - everything is still working afterwards. Hence more often than not binaries - crash when they are run. - - The speed decrease is about 15-35%, depending on the optimization options - used with afl-dyninst. - - So if Dyninst works, it is the best option available. Otherwise it just - doesn't work well. - - [https://github.com/vanhauser-thc/afl-dyninst](https://github.com/vanhauser-thc/afl-dyninst) - - -## RETROWRITE, ZAFL, ... other binary rewriter - - If you have an x86/x86_64 binary that still has its symbols, is compiled - with position independant code (PIC/PIE) and does not use most of the C++ - features then the retrowrite solution might be for you. - It decompiles to ASM files which can then be instrumented with afl-gcc. - - It is at about 80-85% performance. - - [https://git.zephyr-software.com/opensrc/zafl](https://git.zephyr-software.com/opensrc/zafl) - [https://github.com/HexHive/retrowrite](https://github.com/HexHive/retrowrite) - - -## MCSEMA - - Theoretically you can also decompile to llvm IR with mcsema, and then - use llvm_mode to instrument the binary. - Good luck with that. - - [https://github.com/lifting-bits/mcsema](https://github.com/lifting-bits/mcsema) - - -## INTEL-PT - - If you have a newer Intel CPU, you can make use of Intels processor trace. - The big issue with Intel's PT is the small buffer size and the complex - encoding of the debug information collected through PT. - This makes the decoding very CPU intensive and hence slow. - As a result, the overall speed decrease is about 70-90% (depending on - the implementation and other factors). - - There are two AFL intel-pt implementations: - - 1. [https://github.com/junxzm1990/afl-pt](https://github.com/junxzm1990/afl-pt) - => this needs Ubuntu 14.04.05 without any updates and the 4.4 kernel. - - 2. [https://github.com/hunter-ht-2018/ptfuzzer](https://github.com/hunter-ht-2018/ptfuzzer) - => this needs a 4.14 or 4.15 kernel. the "nopti" kernel boot option must - be used. This one is faster than the other. - - Note that there is also honggfuzz: https://github.com/google/honggfuzz - But its IPT performance is just 6%! - - -## CORESIGHT - - Coresight is ARM's answer to Intel's PT. - There is no implementation so far which handles coresight and getting - it working on an ARM Linux is very difficult due to custom kernel building - on embedded systems is difficult. And finding one that has coresight in - the ARM chip is difficult too. - My guess is that it is slower than Qemu, but faster than Intel PT. - - If anyone finds any coresight implementation for AFL please ping me: vh@thc.org - - -## PIN & DYNAMORIO - - Pintool and Dynamorio are dynamic instrumentation engines, and they can be - used for getting basic block information at runtime. - Pintool is only available for Intel x32/x64 on Linux, Mac OS and Windows, - whereas Dynamorio is additionally available for ARM and AARCH64. - Dynamorio is also 10x faster than Pintool. - - The big issue with Dynamorio (and therefore Pintool too) is speed. - Dynamorio has a speed decrease of 98-99% - Pintool has a speed decrease of 99.5% - - Hence Dynamorio is the option to go for if everything else fails, and Pintool - only if Dynamorio fails too. - - Dynamorio solutions: - * [https://github.com/vanhauser-thc/afl-dynamorio](https://github.com/vanhauser-thc/afl-dynamorio) - * [https://github.com/mxmssh/drAFL](https://github.com/mxmssh/drAFL) - * [https://github.com/googleprojectzero/winafl/](https://github.com/googleprojectzero/winafl/) <= very good but windows only - - Pintool solutions: - * [https://github.com/vanhauser-thc/afl-pin](https://github.com/vanhauser-thc/afl-pin) - * [https://github.com/mothran/aflpin](https://github.com/mothran/aflpin) - * [https://github.com/spinpx/afl_pin_mode](https://github.com/spinpx/afl_pin_mode) <= only old Pintool version supported - - -## Non-AFL solutions - - There are many binary-only fuzzing frameworks. - Some are great for CTFs but don't work with large binaries, others are very - slow but have good path discovery, some are very hard to set-up ... - - * QSYM: [https://github.com/sslab-gatech/qsym](https://github.com/sslab-gatech/qsym) - * Manticore: [https://github.com/trailofbits/manticore](https://github.com/trailofbits/manticore) - * S2E: [https://github.com/S2E](https://github.com/S2E) - * Tinyinst: [https://github.com/googleprojectzero/TinyInst](https://github.com/googleprojectzero/TinyInst) (Mac/Windows only) - * Jackalope: [https://github.com/googleprojectzero/Jackalope](https://github.com/googleprojectzero/Jackalope) - * ... please send me any missing that are good - - -## Closing words - - That's it! News, corrections, updates? Send an email to vh@thc.org diff --git a/docs/custom_mutators.md b/docs/custom_mutators.md index 8b5a4068..7b4e0516 100644 --- a/docs/custom_mutators.md +++ b/docs/custom_mutators.md @@ -1,16 +1,16 @@ # Custom Mutators in AFL++ This file describes how you can implement custom mutations to be used in AFL. -For now, we support C/C++ library and Python module, collectivelly named as the +For now, we support C/C++ library and Python module, collectively named as the custom mutator. -There is also experimental support for Rust in `custom_mutators/rust`. -Please refer to that directory for documentation. -Run ```cargo doc -p custom_mutator --open``` in that directory to view the -documentation in your web browser. +There is also experimental support for Rust in `custom_mutators/rust`. For +documentation, refer to that directory. Run `cargo doc -p custom_mutator --open` +in that directory to view the documentation in your web browser. Implemented by -- C/C++ library (`*.so`): Khaled Yakdan from Code Intelligence (<yakdan@code-intelligence.de>) +- C/C++ library (`*.so`): Khaled Yakdan from Code Intelligence + (<yakdan@code-intelligence.de>) - Python module: Christian Holler from Mozilla (<choller@mozilla.com>) ## 1) Introduction @@ -21,13 +21,17 @@ fuzzing by using libraries that perform mutations according to a given grammar. The custom mutator is passed to `afl-fuzz` via the `AFL_CUSTOM_MUTATOR_LIBRARY` or `AFL_PYTHON_MODULE` environment variable, and must export a fuzz function. -Now AFL also supports multiple custom mutators which can be specified in the same `AFL_CUSTOM_MUTATOR_LIBRARY` environment variable like this. +Now AFL++ also supports multiple custom mutators which can be specified in the +same `AFL_CUSTOM_MUTATOR_LIBRARY` environment variable like this. + ```bash export AFL_CUSTOM_MUTATOR_LIBRARY="full/path/to/mutator_first.so;full/path/to/mutator_second.so" ``` -Please see [APIs](#2-apis) and [Usage](#3-usage) for detail. -The custom mutation stage is set to be the first non-deterministic stage (right before the havoc stage). +For details, see [APIs](#2-apis) and [Usage](#3-usage). + +The custom mutation stage is set to be the first non-deterministic stage (right +before the havoc stage). Note: If `AFL_CUSTOM_MUTATOR_ONLY` is set, all mutations will solely be performed with the custom mutator. @@ -35,6 +39,7 @@ performed with the custom mutator. ## 2) APIs C/C++: + ```c void *afl_custom_init(afl_state_t *afl, unsigned int seed); unsigned int afl_custom_fuzz_count(void *data, const unsigned char *buf, size_t buf_size); @@ -53,6 +58,7 @@ void afl_custom_deinit(void *data); ``` Python: + ```python def init(seed): pass @@ -101,7 +107,8 @@ def deinit(): # optional for Python - `init`: - This method is called when AFL++ starts up and is used to seed RNG and set up buffers and state. + This method is called when AFL++ starts up and is used to seed RNG and set + up buffers and state. - `queue_get` (optional): @@ -110,27 +117,26 @@ def deinit(): # optional for Python - `fuzz_count` (optional): - When a queue entry is selected to be fuzzed, afl-fuzz selects the number - of fuzzing attempts with this input based on a few factors. - If however the custom mutator wants to set this number instead on how often - it is called for a specific queue entry, use this function. - This function is most useful if `AFL_CUSTOM_MUTATOR_ONLY` is **not** used. + When a queue entry is selected to be fuzzed, afl-fuzz selects the number of + fuzzing attempts with this input based on a few factors. If, however, the + custom mutator wants to set this number instead on how often it is called + for a specific queue entry, use this function. This function is most useful + if `AFL_CUSTOM_MUTATOR_ONLY` is **not** used. - `fuzz` (optional): This method performs custom mutations on a given input. It also accepts an - additional test case. - Note that this function is optional - but it makes sense to use it. - You would only skip this if `post_process` is used to fix checksums etc. - so if you are using it e.g. as a post processing library. + additional test case. Note that this function is optional - but it makes + sense to use it. You would only skip this if `post_process` is used to fix + checksums etc. so if you are using it, e.g., as a post processing library. Note that a length > 0 *must* be returned! - `describe` (optional): - When this function is called, it shall describe the current testcase, - generated by the last mutation. This will be called, for example, - to name the written testcase file after a crash occurred. - Using it can help to reproduce crashing mutations. + When this function is called, it shall describe the current test case, + generated by the last mutation. This will be called, for example, to name + the written test case file after a crash occurred. Using it can help to + reproduce crashing mutations. - `havoc_mutation` and `havoc_mutation_probability` (optional): @@ -142,21 +148,21 @@ def deinit(): # optional for Python - `post_process` (optional): For some cases, the format of the mutated data returned from the custom - mutator is not suitable to directly execute the target with this input. - For example, when using libprotobuf-mutator, the data returned is in a - protobuf format which corresponds to a given grammar. In order to execute - the target, the protobuf data must be converted to the plain-text format - expected by the target. In such scenarios, the user can define the - `post_process` function. This function is then transforming the data into the - format expected by the API before executing the target. + mutator is not suitable to directly execute the target with this input. For + example, when using libprotobuf-mutator, the data returned is in a protobuf + format which corresponds to a given grammar. In order to execute the target, + the protobuf data must be converted to the plain-text format expected by the + target. In such scenarios, the user can define the `post_process` function. + This function is then transforming the data into the format expected by the + API before executing the target. This can return any python object that implements the buffer protocol and supports PyBUF_SIMPLE. These include bytes, bytearray, etc. - `queue_new_entry` (optional): - This methods is called after adding a new test case to the queue. - If the contents of the file was changed return True, False otherwise. + This methods is called after adding a new test case to the queue. If the + contents of the file was changed, return True, False otherwise. - `introspection` (optional): @@ -168,8 +174,8 @@ def deinit(): # optional for Python The last method to be called, deinitializing the state. -Note that there are also three functions for trimming as described in the -next section. +Note that there are also three functions for trimming as described in the next +section. ### Trimming Support @@ -177,8 +183,8 @@ The generic trimming routines implemented in AFL++ can easily destroy the structure of complex formats, possibly leading to a point where you have a lot of test cases in the queue that your Python module cannot process anymore but your target application still accepts. This is especially the case when your -target can process a part of the input (causing coverage) and then errors out -on the remaining input. +target can process a part of the input (causing coverage) and then errors out on +the remaining input. In such cases, it makes sense to implement a custom trimming routine. The API consists of multiple methods because after each trimming step, we have to go @@ -189,8 +195,9 @@ trimmed input. Here's a quick API description: This method is called at the start of each trimming operation and receives the initial buffer. It should return the amount of iteration steps possible - on this input (e.g. if your input has n elements and you want to remove them - one by one, return n, if you do a binary search, return log(n), and so on). + on this input (e.g., if your input has n elements and you want to remove + them one by one, return n, if you do a binary search, return log(n), and so + on). If your trimming algorithm doesn't allow to determine the amount of (remaining) steps easily (esp. while running), then you can alternatively @@ -202,21 +209,21 @@ trimmed input. Here's a quick API description: - `trim` (optional) This method is called for each trimming operation. It doesn't have any - arguments because we already have the initial buffer from `init_trim` and we - can memorize the current state in the data variables. This can also save + arguments because there is already the initial buffer from `init_trim` and + we can memorize the current state in the data variables. This can also save reparsing steps for each iteration. It should return the trimmed input buffer. - `post_trim` (optional) This method is called after each trim operation to inform you if your - trimming step was successful or not (in terms of coverage). If you receive - a failure here, you should reset your input to the last known good state. - In any case, this method must return the next trim iteration index (from 0 - to the maximum amount of steps you returned in `init_trim`). + trimming step was successful or not (in terms of coverage). If you receive a + failure here, you should reset your input to the last known good state. In + any case, this method must return the next trim iteration index (from 0 to + the maximum amount of steps you returned in `init_trim`). Omitting any of three trimming methods will cause the trimming to be disabled -and trigger a fallback to the builtin default trimming routine. +and trigger a fallback to the built-in default trimming routine. ### Environment Variables @@ -224,11 +231,10 @@ Optionally, the following environment variables are supported: - `AFL_CUSTOM_MUTATOR_ONLY` - Disable all other mutation stages. This can prevent broken testcases - (those that your Python module can't work with anymore) to fill up your - queue. Best combined with a custom trimming routine (see below) because - trimming can cause the same test breakage like havoc and splice. - + Disable all other mutation stages. This can prevent broken test cases (those + that your Python module can't work with anymore) to fill up your queue. Best + combined with a custom trimming routine (see below) because trimming can + cause the same test breakage like havoc and splice. - `AFL_PYTHON_ONLY` @@ -264,22 +270,27 @@ In case your setup is different, set the necessary variables like this: ### Custom Mutator Preparation For C/C++ mutators, the source code must be compiled as a shared object: + ```bash gcc -shared -Wall -O3 example.c -o example.so ``` -Note that if you specify multiple custom mutators, the corresponding functions will -be called in the order in which they are specified. e.g first `post_process` function of -`example_first.so` will be called and then that of `example_second.so`. + +Note that if you specify multiple custom mutators, the corresponding functions +will be called in the order in which they are specified. E.g., the first +`post_process` function of `example_first.so` will be called and then that of +`example_second.so`. ### Run C/C++ + ```bash export AFL_CUSTOM_MUTATOR_LIBRARY="/full/path/to/example_first.so;/full/path/to/example_second.so" afl-fuzz /path/to/program ``` Python + ```bash export PYTHONPATH=`dirname /full/path/to/example.py` export AFL_PYTHON_MODULE=example @@ -288,8 +299,8 @@ afl-fuzz /path/to/program ## 4) Example -Please see [example.c](../custom_mutators/examples/example.c) and -[example.py](../custom_mutators/examples/example.py) +See [example.c](../custom_mutators/examples/example.c) and +[example.py](../custom_mutators/examples/example.py). ## 5) Other Resources @@ -297,4 +308,4 @@ Please see [example.c](../custom_mutators/examples/example.c) and - [bruce30262/libprotobuf-mutator_fuzzing_learning](https://github.com/bruce30262/libprotobuf-mutator_fuzzing_learning/tree/master/4_libprotobuf_aflpp_custom_mutator) - [thebabush/afl-libprotobuf-mutator](https://github.com/thebabush/afl-libprotobuf-mutator) - [XML Fuzzing@NullCon 2017](https://www.agarri.fr/docs/XML_Fuzzing-NullCon2017-PUBLIC.pdf) - - [A bug detected by AFL + XML-aware mutators](https://bugs.chromium.org/p/chromium/issues/detail?id=930663) + - [A bug detected by AFL + XML-aware mutators](https://bugs.chromium.org/p/chromium/issues/detail?id=930663) \ No newline at end of file diff --git a/docs/docs2.md b/docs/docs2.md new file mode 100644 index 00000000..23ef61c5 --- /dev/null +++ b/docs/docs2.md @@ -0,0 +1,124 @@ +# Restructure AFL++'s documentation - Case Study + +## Problem statement + +AFL++ inherited it's documentation from the original Google AFL project. +Since then it has been massively improved - feature and performance wise - +and although the documenation has likewise been continued it has grown out +of proportion. +The documentation is done by non-natives to the English language, plus +none of us has a writer background. + +We see questions on AFL++ usage on mailing lists (e.g. afl-users), discord +channels, web forums and as issues in our repository. +Most of them could be answered if people would read through all the +documentation. + +This only increases as AFL++ has been on the top of Google's fuzzbench +statistics (which measures the performance of fuzzers) and has been +integrated in Google's oss-fuzz and clusterfuzz - and is in many Unix +packaging repositories, e.g. Debian, FreeBSD, etc. + +AFL++ had 44 (!) documentation files with 13k total lines of content. +This was way too much. + +## Proposal abstract + +AFL++'s documentatin needs a complete overhaul, both on a +organisation/structural level as well as the content. + +Overall the following actions have to be performed: + * Create a better structure of documentation so it is easier to find the + information that is being looked for, combining and/or splitting up the + existing documents as needed. + * Rewrite some documentation to remove duplication. Several information is + present several times in the documentation. These should be removed to + where needed so that we have as little bloat as possible. + * The documents have been written and modified by a lot of different people, + most of them non-native English speaker. Hence an overall review where + parts should be rewritten has to be performed and then the rewrite done. + * Create a cheat-sheet for a very short best-setup build and run of AFL++ + * Pictures explain more than 1000 words. We need at least 4 images that + explain the workflow with AFL++: + - the build workflow + - the fuzzing workflow + - the fuzzing campaign management workflow + - the overall workflow that is an overview of the above + - maybe more? where the technical writes seems it necessary for + understanding. + +Requirements: + * Documentation has to be in Markdown format + * Images have to be either in SVG or PNG format. + * All documentation should be (moved) in(to) docs/ + +## Project description + +We created our proposal by discussing in the team what the issues are and +what was needed to fix it. +This resulted in the [project proposal](https://github.com/AFLplusplus/AFLplusplus/blob/stable/docs/docs.md). + +We did not want to be selected by a writer but select a writer ourselves, so +we combed through the list and reviewed every single one of them. +We were not looking for coders writing technical documentation, but rather +someone who is an experienced writer and has documented experience with +structuring documentation. +Few fit that profile and we sent out messages to 6 people. +We finally decided on Jana because she had a strong background in technical +documentation and structuring information. +She had no technical experience in fuzzing whatsoever, but we saw that as +a plus - of course this made the whole process longer to explain details, +but overall ensured that the documentation can be read by (mostly) everyone. + +We communicated via video calls every few weeks and she kept a public kanban +board about her todos, additional we used a Signal channel. +Her changes were imported via PRs where we discussed details. + +The project was off to a good start, but then Jana got pregnant with serious +side effects that made working impossible for her for a longer time, hence +the schedule was thrown back. +She offered to rescind the payment and we select a new writer, but we saw +little opportunity in that, as that would mean a new selection of a writer, +someone else with a different vision on how the result should look like so +basically a full restart of the project and a large impact on our own time. +So we agreed on - after discussion with the Google GSoD team - that she +continues the project after the GSoD completion deadline as best as she can. + +End of November she took one week off from work and fully dedicated her time +for the documenation which brought the project a big step forward. + +Originally the project should have been ended begin of October, but now - at +nearing the end of November, we are at about 85% completion, with the end +being expected around mid of December. + +## Metrics + +We merged most of the changes in our development branch and are getting +close to a state where the user documentation part is completed and we +can create a new release. Only then the new documentatin is actually visible +to users. Therefore no metrics could be collected so far. + +We plan on a user-assisted QA review end of November/begin of December. + +The documentation was reviewed by a few test users so far however who gave +it a thumbs up. + +## Summary + +The GSoD project itself is great. It helps to get the documentation back in +line. +It was and is a larger time investment from our side, but we expected that. +When the project is done, the documentation will be more accessible by users +and also need less maintenance by us. +There is still follow-up work to be done by us afterwards (web site for the +docs, etc.). + +Not sure what we would do differently next time. I think we prepared best as +possible and reacted best as possible to the unexpected. + +Recommendations for other organizations who would like to participate in GSoD: + - expect the process to take a larger part of your time. the writer needs + your full support. + - have someone dedicated from the dev/org side to support, educate and + supervice the writer + - set clear goals and expectations diff --git a/docs/env_variables.md b/docs/env_variables.md index 0686f1a8..c45f4ab9 100644 --- a/docs/env_variables.md +++ b/docs/env_variables.md @@ -1,88 +1,78 @@ -# Environmental variables +# Environment variables - This document discusses the environment variables used by American Fuzzy Lop++ - to expose various exotic functions that may be (rarely) useful for power - users or for some types of custom fuzzing setups. See [README.md](README.md) for the general - instruction manual. + This document discusses the environment variables used by AFL++ to expose + various exotic functions that may be (rarely) useful for power users or for + some types of custom fuzzing setups. For general information about AFL++, see + [README.md](../README.md). - Note that most tools will warn on any unknown AFL environment variables. - This is for warning on typos that can happen. If you want to disable this - check then set the `AFL_IGNORE_UNKNOWN_ENVS` environment variable. + Note: Most tools will warn on any unknown AFL++ environment variables; for + example, because of typos. If you want to disable this check, then set the + `AFL_IGNORE_UNKNOWN_ENVS` environment variable. ## 1) Settings for all compilers -Starting with AFL++ 3.0 there is only one compiler: afl-cc -To select the different instrumentation modes this can be done by - 1. passing the --afl-MODE command line option to the compiler - 2. or using a symlink to afl-cc: afl-gcc, afl-g++, afl-clang, afl-clang++, - afl-clang-fast, afl-clang-fast++, afl-clang-lto, afl-clang-lto++, - afl-gcc-fast, afl-g++-fast - 3. or using the environment variable `AFL_CC_COMPILER` with `MODE` - -`MODE` can be one of `LTO` (afl-clang-lto*), `LLVM` (afl-clang-fast*), `GCC_PLUGIN` -(afl-g*-fast) or `GCC` (afl-gcc/afl-g++). - -Because (with the exception of the --afl-MODE command line option) the -compile-time tools do not accept AFL specific command-line options, they -make fairly broad use of environmental variables instead: - - - Some build/configure scripts break with AFL++ compilers. To be able to - pass them, do: -``` - export CC=afl-cc - export CXX=afl-c++ - export AFL_NOOPT=1 - ./configure --disable-shared --disabler-werror - unset AFL_NOOPT - make -``` - - - Most AFL tools do not print any output if stdout/stderr are redirected. - If you want to get the output into a file then set the `AFL_DEBUG` - environment variable. - This is sadly necessary for various build processes which fail otherwise. +Starting with AFL++ 3.0, there is only one compiler: afl-cc. + +To select the different instrumentation modes, use one of the following options: + + - Pass the --afl-MODE command-line option to the compiler. Only this option + accepts further AFL-specific command-line options. + - Use a symlink to afl-cc: afl-clang, afl-clang++, afl-clang-fast, + afl-clang-fast++, afl-clang-lto, afl-clang-lto++, afl-g++, afl-g++-fast, + afl-gcc, afl-gcc-fast. This option does not accept AFL-specific command-line + options. Instead, use environment variables. + - Use the `AFL_CC_COMPILER` environment variable with `MODE`. To select + `MODE`, use one of the following values: + + - `GCC` (afl-gcc/afl-g++) + - `GCC_PLUGIN` (afl-g*-fast) + - `LLVM` (afl-clang-fast*) + - `LTO` (afl-clang-lto*). + +The compile-time tools do not accept AFL-specific command-line options. The +--afl-MODE command line option is the only exception. The other options make +fairly broad use of environment variables instead: + + - Some build/configure scripts break with AFL++ compilers. To be able to pass + them, do: + + ``` + export CC=afl-cc + export CXX=afl-c++ + export AFL_NOOPT=1 + ./configure --disable-shared --disabler-werror + unset AFL_NOOPT + make + ``` + + - Setting `AFL_AS`, `AFL_CC`, and `AFL_CXX` lets you use alternate downstream + compilation tools, rather than the default 'as', 'clang', or 'gcc' binaries + in your `$PATH`. + + - If you are a weird person that wants to compile and instrument asm text + files, then use the `AFL_AS_FORCE_INSTRUMENT` variable: + `AFL_AS_FORCE_INSTRUMENT=1 afl-gcc foo.s -o foo` + + - Most AFL tools do not print any output if stdout/stderr are redirected. If + you want to get the output into a file, then set the `AFL_DEBUG` environment + variable. This is sadly necessary for various build processes which fail + otherwise. + + - By default, the wrapper appends `-O3` to optimize builds. Very rarely, this + will cause problems in programs built with -Werror, because `-O3` enables + more thorough code analysis and can spew out additional warnings. To disable + optimizations, set `AFL_DONT_OPTIMIZE`. However, if `-O...` and/or + `-fno-unroll-loops` are set, these are not overridden. - Setting `AFL_HARDEN` automatically adds code hardening options when invoking the downstream compiler. This currently includes `-D_FORTIFY_SOURCE=2` and `-fstack-protector-all`. The setting is useful for catching non-crashing memory bugs at the expense of a very slight (sub-5%) performance loss. - - By default, the wrapper appends `-O3` to optimize builds. Very rarely, this - will cause problems in programs built with -Werror, simply because `-O3` - enables more thorough code analysis and can spew out additional warnings. - To disable optimizations, set `AFL_DONT_OPTIMIZE`. - However if `-O...` and/or `-fno-unroll-loops` are set, these are not - overridden. - - - Setting `AFL_USE_ASAN` automatically enables ASAN, provided that your - compiler supports it. - - (You can also enable MSAN via `AFL_USE_MSAN`; ASAN and MSAN come with the - same gotchas; the modes are mutually exclusive. UBSAN can be enabled - similarly by setting the environment variable `AFL_USE_UBSAN=1`. Finally - there is the Control Flow Integrity sanitizer that can be activated by - `AFL_USE_CFISAN=1`) - - - Setting `AFL_USE_LSAN` automatically enables Leak-Sanitizer, provided - that your compiler supports it. To perform a leak check within your - program at a certain point (such as at the end of an __AFL_LOOP), - you can run the macro __AFL_LEAK_CHECK(); which will cause - an abort if any memory is leaked (you can combine this with the - LSAN_OPTIONS=suppressions option to supress some known leaks). - - - Setting `AFL_CC`, `AFL_CXX`, and `AFL_AS` lets you use alternate downstream - compilation tools, rather than the default 'clang', 'gcc', or 'as' binaries - in your `$PATH`. - - - `AFL_PATH` can be used to point afl-gcc to an alternate location of afl-as. - One possible use of this is utils/clang_asm_normalize/, which lets - you instrument hand-written assembly when compiling clang code by plugging - a normalizer into the chain. (There is no equivalent feature for GCC.) - - Setting `AFL_INST_RATIO` to a percentage between 0 and 100 controls the - probability of instrumenting every branch. This is (very rarely) useful - when dealing with exceptionally complex programs that saturate the output - bitmap. Examples include v8, ffmpeg, and perl. + probability of instrumenting every branch. This is (very rarely) useful when + dealing with exceptionally complex programs that saturate the output bitmap. + Examples include ffmpeg, perl, and v8. (If this ever happens, afl-fuzz will warn you ahead of the time by displaying the "bitmap density" field in fiery red.) @@ -90,493 +80,612 @@ make fairly broad use of environmental variables instead: Setting `AFL_INST_RATIO` to 0 is a valid choice. This will instrument only the transitions between function entry points, but not individual branches. - Note that this is an outdated variable. A few instances (e.g. afl-gcc) - still support these, but state-of-the-art (e.g. LLVM LTO and LLVM PCGUARD) + Note that this is an outdated variable. A few instances (e.g., afl-gcc) + still support these, but state-of-the-art (e.g., LLVM LTO and LLVM PCGUARD) do not need this. - `AFL_NO_BUILTIN` causes the compiler to generate code suitable for use with libtokencap.so (but perhaps running a bit slower than without the flag). + - `AFL_PATH` can be used to point afl-gcc to an alternate location of afl-as. + One possible use of this is utils/clang_asm_normalize/, which lets you + instrument hand-written assembly when compiling clang code by plugging a + normalizer into the chain. (There is no equivalent feature for GCC.) + + - Setting `AFL_QUIET` will prevent afl-as and afl-cc banners from being + displayed during compilation, in case you find them distracting. + + - Setting `AFL_USE_...` automatically enables supported sanitizers - provided + that your compiler supports it. Available are: + - `AFL_USE_ASAN=1` - activates the address sanitizer (memory corruption + detection) + - `AFL_USE_CFISAN=1` - activates the Control Flow Integrity sanitizer (e.g. + type confusion vulnerabilities) + - `AFL_USE_LSAN` - activates the leak sanitizer. To perform a leak check + within your program at a certain point (such as at the end of an + `__AFL_LOOP()`), you can run the macro `__AFL_LEAK_CHECK();` which will + cause an abort if any memory is leaked (you can combine this with the + `LSAN_OPTIONS=...` suppression option to suppress some known leaks). + - `AFL_USE_MSAN=1` - activates the memory sanitizer (uninitialized memory) + - `AFL_USE_TSAN=1` - activates the thread sanitizer to find thread race + conditions + - `AFL_USE_UBSAN=1` - activates the undefined behavior sanitizer + - `TMPDIR` is used by afl-as for temporary files; if this variable is not set, the tool defaults to /tmp. - - If you are a weird person that wants to compile and instrument asm - text files then use the `AFL_AS_FORCE_INSTRUMENT` variable: - `AFL_AS_FORCE_INSTRUMENT=1 afl-gcc foo.s -o foo` +## 2) Settings for LLVM and LTO: afl-clang-fast / afl-clang-fast++ / afl-clang-lto / afl-clang-lto++ - - Setting `AFL_QUIET` will prevent afl-cc and afl-as banners from being - displayed during compilation, in case you find them distracting. +The native instrumentation helpers (instrumentation and gcc_plugin) accept a +subset of the settings discussed in section 1, with the exception of: -## 2) Settings for LLVM and LTO: afl-clang-fast / afl-clang-fast++ / afl-clang-lto / afl-clang-lto++ + - `AFL_AS`, since this toolchain does not directly invoke GNU `as`. -The native instrumentation helpers (instrumentation and gcc_plugin) accept a subset -of the settings discussed in section 1, with the exception of: + - `AFL_INST_RATIO`, as we use collision free instrumentation by default. Not + all passes support this option though as it is an outdated feature. - LLVM modes support `AFL_LLVM_DICT2FILE=/absolute/path/file.txt` which will - write all constant string comparisons to this file to be used later with + write all constant string comparisons to this file to be used later with afl-fuzz' `-x` option. - - `AFL_AS`, since this toolchain does not directly invoke GNU as. - - `TMPDIR` and `AFL_KEEP_ASSEMBLY`, since no temporary assembly files are created. - - `AFL_INST_RATIO`, as we by default use collision free instrumentation. - Not all passes support this option though as it is an outdated feature. - -Then there are a few specific features that are only available in instrumentation mode: +Then there are a few specific features that are only available in +instrumentation mode: ### Select the instrumentation mode - - `AFL_LLVM_INSTRUMENT` - this configures the instrumentation mode. - Available options: - PCGUARD - our own pcgard based instrumentation (default) - NATIVE - clang's original pcguard based instrumentation - CLASSIC - classic AFL (map[cur_loc ^ prev_loc >> 1]++) (default) - LTO - LTO instrumentation (see below) - CTX - context sensitive instrumentation (see below) - NGRAM-x - deeper previous location coverage (from NGRAM-2 up to NGRAM-16) - GCC - outdated gcc instrumentation - CLANG - outdated clang instrumentation - In CLASSIC you can also specify CTX and/or NGRAM, seperate the options - with a comma "," then, e.g.: - `AFL_LLVM_INSTRUMENT=CLASSIC,CTX,NGRAM-4` - Note that this is actually not a good idea to use both CTX and NGRAM :) +`AFL_LLVM_INSTRUMENT` - this configures the instrumentation mode. + +Available options: + + - CLANG - outdated clang instrumentation + - CLASSIC - classic AFL (map[cur_loc ^ prev_loc >> 1]++) (default) + + You can also specify CTX and/or NGRAM, separate the options with a comma "," + then, e.g.: `AFL_LLVM_INSTRUMENT=CLASSIC,CTX,NGRAM-4` -### LTO + Note: It is actually not a good idea to use both CTX and NGRAM. :) + - CTX - context sensitive instrumentation + - GCC - outdated gcc instrumentation + - LTO - LTO instrumentation + - NATIVE - clang's original pcguard based instrumentation + - NGRAM-x - deeper previous location coverage (from NGRAM-2 up to NGRAM-16) + - PCGUARD - our own pcgard based instrumentation (default) - This is a different kind way of instrumentation: first it compiles all - code in LTO (link time optimization) and then performs an edge inserting - instrumentation which is 100% collision free (collisions are a big issue - in AFL and AFL-like instrumentations). This is performed by using - afl-clang-lto/afl-clang-lto++ instead of afl-clang-fast, but is only - built if LLVM 11 or newer is used. +#### CMPLOG - - `AFL_LLVM_INSTRUMENT=CFG` will use Control Flow Graph instrumentation. - (not recommended for afl-clang-fast, default for afl-clang-lto as there - it is a different and better kind of instrumentation.) +Setting `AFL_LLVM_CMPLOG=1` during compilation will tell afl-clang-fast to +produce a CmpLog binary. - None of the following options are necessary to be used and are rather for - manual use (which only ever the author of this LTO implementation will use). - These are used if several separated instrumentations are performed which - are then later combined. +For more information, see +[instrumentation/README.cmplog.md](../instrumentation/README.cmplog.md). - - `AFL_LLVM_DOCUMENT_IDS=file` will document to a file which edge ID was given - to which function. This helps to identify functions with variable bytes - or which functions were touched by an input. - - `AFL_LLVM_MAP_ADDR` sets the fixed map address to a different address than - the default `0x10000`. A value of 0 or empty sets the map address to be - dynamic (the original AFL way, which is slower) - - `AFL_LLVM_MAP_DYNAMIC` sets the shared memory address to be dynamic - - `AFL_LLVM_LTO_STARTID` sets the starting location ID for the instrumentation. - This defaults to 1 - - `AFL_LLVM_LTO_DONTWRITEID` prevents that the highest location ID written - into the instrumentation is set in a global variable +#### CTX - See [instrumentation/README.lto.md](../instrumentation/README.lto.md) for more information. +Setting `AFL_LLVM_CTX` or `AFL_LLVM_INSTRUMENT=CTX` activates context sensitive +branch coverage - meaning that each edge is additionally combined with its +caller. It is highly recommended to increase the `MAP_SIZE_POW2` definition in +config.h to at least 18 and maybe up to 20 for this as otherwise too many map +collisions occur. -### NGRAM +For more information, see +[instrumentation/README.llvm.md#6) AFL++ Context Sensitive Branch Coverage](../instrumentation/README.llvm.md#6-afl-context-sensitive-branch-coverage). - - Setting `AFL_LLVM_NGRAM_SIZE` or `AFL_LLVM_INSTRUMENT=NGRAM-{value}` - activates ngram prev_loc coverage, good values are 2, 4 or 8 - (any value between 2 and 16 is valid). - It is highly recommended to increase the `MAP_SIZE_POW2` definition in - config.h to at least 18 and maybe up to 20 for this as otherwise too - many map collisions occur. +#### INSTRUMENT LIST (selectively instrument files and functions) - See [instrumentation/README.ngram.md](../instrumentation/README.ngram.md) +This feature allows selective instrumentation of the source. -### CTX +Setting `AFL_LLVM_ALLOWLIST` or `AFL_LLVM_DENYLIST` with a file name and/or +function will only instrument (or skip) those files that match the names listed +in the specified file. - - Setting `AFL_LLVM_CTX` or `AFL_LLVM_INSTRUMENT=CTX` - activates context sensitive branch coverage - meaning that each edge - is additionally combined with its caller. - It is highly recommended to increase the `MAP_SIZE_POW2` definition in - config.h to at least 18 and maybe up to 20 for this as otherwise too - many map collisions occur. +For more information, see +[instrumentation/README.instrument_list.md](../instrumentation/README.instrument_list.md). - See [instrumentation/README.ctx.md](../instrumentation/README.ctx.md) +#### LAF-INTEL -### LAF-INTEL +This great feature will split compares into series of single byte comparisons to +allow afl-fuzz to find otherwise rather impossible paths. It is not restricted +to Intel CPUs. ;-) - This great feature will split compares into series of single byte comparisons - to allow afl-fuzz to find otherwise rather impossible paths. It is not - restricted to Intel CPUs ;-) + - Setting `AFL_LLVM_LAF_TRANSFORM_COMPARES` will split string compare + functions. - - Setting `AFL_LLVM_LAF_TRANSFORM_COMPARES` will split string compare functions + - Setting `AFL_LLVM_LAF_SPLIT_COMPARES` will split all floating point and 64, + 32 and 16 bit integer CMP instructions. - - Setting `AFL_LLVM_LAF_SPLIT_SWITCHES` will split all `switch` constructs + - Setting `AFL_LLVM_LAF_SPLIT_FLOATS` will split floating points, needs + `AFL_LLVM_LAF_SPLIT_COMPARES` to be set. - - Setting `AFL_LLVM_LAF_SPLIT_COMPARES` will split all floating point and - 64, 32 and 16 bit integer CMP instructions + - Setting `AFL_LLVM_LAF_SPLIT_SWITCHES` will split all `switch` constructs. - - Setting `AFL_LLVM_LAF_SPLIT_FLOATS` will split floating points, needs - AFL_LLVM_LAF_SPLIT_COMPARES to be set + - Setting `AFL_LLVM_LAF_ALL` sets all of the above. - - Setting `AFL_LLVM_LAF_ALL` sets all of the above +For more information, see +[instrumentation/README.laf-intel.md](../instrumentation/README.laf-intel.md). - See [instrumentation/README.laf-intel.md](../instrumentation/README.laf-intel.md) for more information. +#### LTO -### INSTRUMENT LIST (selectively instrument files and functions) +This is a different way of instrumentation: first it compiles all code in LTO +(link time optimization) and then performs an edge inserting instrumentation +which is 100% collision free (collisions are a big issue in AFL and AFL-like +instrumentations). This is performed by using afl-clang-lto/afl-clang-lto++ +instead of afl-clang-fast, but is only built if LLVM 11 or newer is used. - This feature allows selective instrumentation of the source +`AFL_LLVM_INSTRUMENT=CFG` will use Control Flow Graph instrumentation. (Not +recommended for afl-clang-fast, default for afl-clang-lto as there it is a +different and better kind of instrumentation.) - - Setting `AFL_LLVM_ALLOWLIST` or `AFL_LLVM_DENYLIST` with a filenames and/or - function will only instrument (or skip) those files that match the names - listed in the specified file. +None of the following options are necessary to be used and are rather for manual +use (which only ever the author of this LTO implementation will use). These are +used if several separated instrumentations are performed which are then later +combined. - See [instrumentation/README.instrument_list.md](../instrumentation/README.instrument_list.md) for more information. + - `AFL_LLVM_DOCUMENT_IDS=file` will document to a file which edge ID was given + to which function. This helps to identify functions with variable bytes or + which functions were touched by an input. + - `AFL_LLVM_LTO_DONTWRITEID` prevents that the highest location ID written + into the instrumentation is set in a global variable. + - `AFL_LLVM_LTO_STARTID` sets the starting location ID for the + instrumentation. This defaults to 1. + - `AFL_LLVM_MAP_ADDR` sets the fixed map address to a different address than + the default `0x10000`. A value of 0 or empty sets the map address to be + dynamic (the original AFL way, which is slower). + - `AFL_LLVM_MAP_DYNAMIC` sets the shared memory address to be dynamic. -### Thread safe instrumentation counters (in all modes) + For more information, see + [instrumentation/README.lto.md](../instrumentation/README.lto.md). - - Setting `AFL_LLVM_THREADSAFE_INST` will inject code that implements thread - safe counters. The overhead is a little bit higher compared to the older - non-thread safe case. Note that this disables neverzero (see below). +#### NGRAM -### NOT_ZERO +Setting `AFL_LLVM_INSTRUMENT=NGRAM-{value}` or `AFL_LLVM_NGRAM_SIZE` activates +ngram prev_loc coverage. Good values are 2, 4, or 8 (any value between 2 and 16 +is valid). It is highly recommended to increase the `MAP_SIZE_POW2` definition +in config.h to at least 18 and maybe up to 20 for this as otherwise too many map +collisions occur. - - Setting `AFL_LLVM_NOT_ZERO=1` during compilation will use counters - that skip zero on overflow. This is the default for llvm >= 9, - however for llvm versions below that this will increase an unnecessary - slowdown due a performance issue that is only fixed in llvm 9+. - This feature increases path discovery by a little bit. +For more information, see +[instrumentation/README.llvm.md#7) AFL++ N-Gram Branch Coverage](../instrumentation/README.llvm.md#7-afl-n-gram-branch-coverage). - - Setting `AFL_LLVM_SKIP_NEVERZERO=1` will not implement the skip zero - test. If the target performs only few loops then this will give a - small performance boost. +#### NOT_ZERO - See [instrumentation/README.neverzero.md](../instrumentation/README.neverzero.md) + - Setting `AFL_LLVM_NOT_ZERO=1` during compilation will use counters that skip + zero on overflow. This is the default for llvm >= 9, however, for llvm + versions below that this will increase an unnecessary slowdown due a + performance issue that is only fixed in llvm 9+. This feature increases path + discovery by a little bit. -### CMPLOG + - Setting `AFL_LLVM_SKIP_NEVERZERO=1` will not implement the skip zero test. + If the target performs only a few loops, then this will give a small + performance boost. - - Setting `AFL_LLVM_CMPLOG=1` during compilation will tell afl-clang-fast to - produce a CmpLog binary. +#### Thread safe instrumentation counters (in all modes) - See [instrumentation/README.cmplog.md](../instrumentation/README.cmplog.md) +Setting `AFL_LLVM_THREADSAFE_INST` will inject code that implements thread safe +counters. The overhead is a little bit higher compared to the older non-thread +safe case. Note that this disables neverzero (see NOT_ZERO). ## 3) Settings for GCC / GCC_PLUGIN modes -Then there are a few specific features that are only available in GCC and -GCC_PLUGIN mode. +There are a few specific features that are only available in GCC and GCC_PLUGIN +mode. + + - GCC mode only: Setting `AFL_KEEP_ASSEMBLY` prevents afl-as from deleting + instrumented assembly files. Useful for troubleshooting problems or + understanding how the tool works. - - Setting `AFL_KEEP_ASSEMBLY` prevents afl-as from deleting instrumented - assembly files. Useful for troubleshooting problems or understanding how - the tool works. (GCC mode only) To get them in a predictable place, try something like: -``` + + ``` mkdir assembly_here TMPDIR=$PWD/assembly_here AFL_KEEP_ASSEMBLY=1 make clean all -``` - - Setting `AFL_GCC_INSTRUMENT_FILE` with a filename will only instrument those - files that match the names listed in this file (one filename per line). - See [instrumentation/README.instrument_list.md](../instrumentation/README.instrument_list.md) for more information. - (GCC_PLUGIN mode only) + ``` + + - GCC_PLUGIN mode only: Setting `AFL_GCC_INSTRUMENT_FILE` with a filename will + only instrument those files that match the names listed in this file (one + filename per line). See + [instrumentation/README.instrument_list.md](../instrumentation/README.instrument_list.md) + for more information. ## 4) Settings for afl-fuzz The main fuzzer binary accepts several options that disable a couple of sanity checks or alter some of the more exotic semantics of the tool: - - Setting `AFL_SKIP_CPUFREQ` skips the check for CPU scaling policy. This is - useful if you can't change the defaults (e.g., no root access to the - system) and are OK with some performance loss. - - - `AFL_EXIT_WHEN_DONE` causes afl-fuzz to terminate when all existing paths - have been fuzzed and there were no new finds for a while. This would be - normally indicated by the cycle counter in the UI turning green. May be - convenient for some types of automated jobs. - - - `AFL_EXIT_ON_TIME` Causes afl-fuzz to terminate if no new paths were - found within a specified period of time (in seconds). May be convenient - for some types of automated jobs. - - - `AFL_EXIT_ON_SEED_ISSUES` will restore the vanilla afl-fuzz behaviour - which does not allow crashes or timeout seeds in the initial -i corpus. + - Setting `AFL_AUTORESUME` will resume a fuzz run (same as providing `-i -`) + for an existing out folder, even if a different `-i` was provided. Without + this setting, afl-fuzz will refuse execution for a long-fuzzed out dir. - - `AFL_MAP_SIZE` sets the size of the shared map that afl-fuzz, afl-showmap, - afl-tmin and afl-analyze create to gather instrumentation data from - the target. This must be equal or larger than the size the target was - compiled with. + - Benchmarking only: `AFL_BENCH_JUST_ONE` causes the fuzzer to exit after + processing the first queue entry; and `AFL_BENCH_UNTIL_CRASH` causes it to + exit soon after the first crash is found. - `AFL_CMPLOG_ONLY_NEW` will only perform the expensive cmplog feature for - newly found testcases and not for testcases that are loaded on startup + newly found test cases and not for test cases that are loaded on startup (`-i in`). This is an important feature to set when resuming a fuzzing session. - - `AFL_TESTCACHE_SIZE` allows you to override the size of `#define TESTCASE_CACHE` - in config.h. Recommended values are 50-250MB - or more if your fuzzing - finds a huge amount of paths for large inputs. + - Setting `AFL_CRASH_EXITCODE` sets the exit code AFL++ treats as crash. For + example, if `AFL_CRASH_EXITCODE='-1'` is set, each input resulting in a `-1` + return code (i.e. `exit(-1)` got called), will be treated as if a crash had + occurred. This may be beneficial if you look for higher-level faulty + conditions in which your target still exits gracefully. + + - Setting `AFL_CUSTOM_MUTATOR_LIBRARY` to a shared library with + afl_custom_fuzz() creates additional mutations through this library. If + afl-fuzz is compiled with Python (which is autodetected during building + afl-fuzz), setting `AFL_PYTHON_MODULE` to a Python module can also provide + additional mutations. If `AFL_CUSTOM_MUTATOR_ONLY` is also set, all + mutations will solely be performed with the custom mutator. This feature + allows to configure custom mutators which can be very helpful, e.g., fuzzing + XML or other highly flexible structured input. For details, see + [custom_mutators.md](custom_mutators.md). + + - Setting `AFL_CYCLE_SCHEDULES` will switch to a different schedule every time + a cycle is finished. + + - Setting `AFL_DEBUG_CHILD` will not suppress the child output. This lets you + see all output of the child, making setup issues obvious. For example, in an + unicornafl harness, you might see python stacktraces. You may also see other + logs that way, indicating why the forkserver won't start. Not pretty but + good for debugging purposes. Note that `AFL_DEBUG_CHILD_OUTPUT` is + deprecated. - Setting `AFL_DISABLE_TRIM` tells afl-fuzz not to trim test cases. This is usually a bad idea! - - Setting `AFL_NO_AFFINITY` disables attempts to bind to a specific CPU core - on Linux systems. This slows things down, but lets you run more instances - of afl-fuzz than would be prudent (if you really want to). + - `AFL_EXIT_ON_SEED_ISSUES` will restore the vanilla afl-fuzz behavior which + does not allow crashes or timeout seeds in the initial -i corpus. - - Setting `AFL_TRY_AFFINITY` tries to attempt binding to a specific CPU core - on Linux systems, but will not terminate if that fails. + - `AFL_EXIT_ON_TIME` causes afl-fuzz to terminate if no new paths were found + within a specified period of time (in seconds). May be convenient for some + types of automated jobs. - - Setting `AFL_NO_AUTODICT` will not load an LTO generated auto dictionary - that is compiled into the target. + - `AFL_EXIT_WHEN_DONE` causes afl-fuzz to terminate when all existing paths + have been fuzzed and there were no new finds for a while. This would be + normally indicated by the cycle counter in the UI turning green. May be + convenient for some types of automated jobs. - - Setting `AFL_HANG_TMOUT` allows you to specify a different timeout for - deciding if a particular test case is a "hang". The default is 1 second - or the value of the `-t` parameter, whichever is larger. Dialing the value - down can be useful if you are very concerned about slow inputs, or if you - don't want AFL++ to spend too much time classifying that stuff and just - rapidly put all timeouts in that bin. + - Setting `AFL_EXPAND_HAVOC_NOW` will start in the extended havoc mode that + includes costly mutations. afl-fuzz automatically enables this mode when + deemed useful otherwise. + + - `AFL_FAST_CAL` keeps the calibration stage about 2.5x faster (albeit less + precise), which can help when starting a session against a slow target. + `AFL_CAL_FAST` works too. + + - Setting `AFL_FORCE_UI` will force painting the UI on the screen even if no + valid terminal was detected (for virtual consoles). - Setting `AFL_FORKSRV_INIT_TMOUT` allows you to specify a different timeout to wait for the forkserver to spin up. The default is the `-t` value times `FORK_WAIT_MULT` from `config.h` (usually 10), so for a `-t 100`, the - default would wait for `1000` milliseconds. Setting a different time here is useful - if the target has a very slow startup time, for example when doing - full-system fuzzing or emulation, but you don't want the actual runs - to wait too long for timeouts. + default would wait for `1000` milliseconds. Setting a different time here is + useful if the target has a very slow startup time, for example, when doing + full-system fuzzing or emulation, but you don't want the actual runs to wait + too long for timeouts. - - `AFL_NO_ARITH` causes AFL++ to skip most of the deterministic arithmetics. - This can be useful to speed up the fuzzing of text-based file formats. - - - `AFL_NO_SNAPSHOT` will advice afl-fuzz not to use the snapshot feature - if the snapshot lkm is loaded - - - `AFL_SHUFFLE_QUEUE` randomly reorders the input queue on startup. Requested - by some users for unorthodox parallelized fuzzing setups, but not - advisable otherwise. + - Setting `AFL_HANG_TMOUT` allows you to specify a different timeout for + deciding if a particular test case is a "hang". The default is 1 second or + the value of the `-t` parameter, whichever is larger. Dialing the value down + can be useful if you are very concerned about slow inputs, or if you don't + want AFL++ to spend too much time classifying that stuff and just rapidly + put all timeouts in that bin. - - `AFL_TMPDIR` is used to write the `.cur_input` file to if exists, and in - the normal output directory otherwise. You would use this to point to - a ramdisk/tmpfs. This increases the speed by a small value but also - reduces the stress on SSDs. + - If you are Jakub, you may need `AFL_I_DONT_CARE_ABOUT_MISSING_CRASHES`. + Others need not apply, unless they also want to disable the + `/proc/sys/kernel/core_pattern` check. - - When developing custom instrumentation on top of afl-fuzz, you can use - `AFL_SKIP_BIN_CHECK` to inhibit the checks for non-instrumented binaries - and shell scripts; and `AFL_DUMB_FORKSRV` in conjunction with the `-n` - setting to instruct afl-fuzz to still follow the fork server protocol - without expecting any instrumentation data in return. - Note that this also turns off auto map size detection. + - If afl-fuzz encounters an incorrect fuzzing setup during a fuzzing session + (not at startup), it will terminate. If you do not want this, then you can + set `AFL_IGNORE_PROBLEMS`. - When running in the `-M` or `-S` mode, setting `AFL_IMPORT_FIRST` causes the - fuzzer to import test cases from other instances before doing anything - else. This makes the "own finds" counter in the UI more accurate. - Beyond counter aesthetics, not much else should change. + fuzzer to import test cases from other instances before doing anything else. + This makes the "own finds" counter in the UI more accurate. Beyond counter + aesthetics, not much else should change. + + - `AFL_KILL_SIGNAL`: Set the signal ID to be delivered to child processes on + timeout. Unless you implement your own targets or instrumentation, you + likely don't have to set it. By default, on timeout and on exit, `SIGKILL` + (`AFL_KILL_SIGNAL=9`) will be delivered to the child. + + - `AFL_MAP_SIZE` sets the size of the shared map that afl-analyze, afl-fuzz, + afl-showmap, and afl-tmin create to gather instrumentation data from the + target. This must be equal or larger than the size the target was compiled + with. + + - Setting `AFL_MAX_DET_EXRAS` will change the threshold at what number of + elements in the `-x` dictionary and LTO autodict (combined) the + probabilistic mode will kick off. In probabilistic mode, not all dictionary + entries will be used all of the time for fuzzing mutations to not slow down + fuzzing. The default count is `200` elements. So for the 200 + 1st element, + there is a 1 in 201 chance, that one of the dictionary entries will not be + used directly. - - Note that `AFL_POST_LIBRARY` is deprecated, use `AFL_CUSTOM_MUTATOR_LIBRARY` - instead (see below). + - Setting `AFL_NO_AFFINITY` disables attempts to bind to a specific CPU core + on Linux systems. This slows things down, but lets you run more instances of + afl-fuzz than would be prudent (if you really want to). - - `AFL_KILL_SIGNAL`: Set the signal ID to be delivered to child processes on timeout. - Unless you implement your own targets or instrumentation, you likely don't have to set it. - By default, on timeout and on exit, `SIGKILL` (`AFL_KILL_SIGNAL=9`) will be delivered to the child. + - `AFL_NO_ARITH` causes AFL++ to skip most of the deterministic arithmetics. + This can be useful to speed up the fuzzing of text-based file formats. - - Setting `AFL_CUSTOM_MUTATOR_LIBRARY` to a shared library with - afl_custom_fuzz() creates additional mutations through this library. - If afl-fuzz is compiled with Python (which is autodetected during building - afl-fuzz), setting `AFL_PYTHON_MODULE` to a Python module can also provide - additional mutations. - If `AFL_CUSTOM_MUTATOR_ONLY` is also set, all mutations will solely be - performed with the custom mutator. - This feature allows to configure custom mutators which can be very helpful, - e.g. fuzzing XML or other highly flexible structured input. - Please see [custom_mutators.md](custom_mutators.md). + - Setting `AFL_NO_AUTODICT` will not load an LTO generated auto dictionary + that is compiled into the target. - - `AFL_FAST_CAL` keeps the calibration stage about 2.5x faster (albeit less - precise), which can help when starting a session against a slow target. - `AFL_CAL_FAST` works too. + - Setting `AFL_NO_COLOR` or `AFL_NO_COLOUR` will omit control sequences for + coloring console output when configured with USE_COLOR and not + ALWAYS_COLORED. - The CPU widget shown at the bottom of the screen is fairly simplistic and may complain of high load prematurely, especially on systems with low core - counts. To avoid the alarming red color, you can set `AFL_NO_CPU_RED`. - - - In QEMU mode (-Q) and Frida mode (-O), `AFL_PATH` will - be searched for afl-qemu-trace and afl-frida-trace.so. + counts. To avoid the alarming red color for very high CPU usages, you can + set `AFL_NO_CPU_RED`. - - In QEMU mode (-Q), setting `AFL_QEMU_CUSTOM_BIN` cause afl-fuzz to skip - prepending `afl-qemu-trace` to your command line. Use this if you wish to use a - custom afl-qemu-trace or if you need to modify the afl-qemu-trace arguments. - - - Setting `AFL_CYCLE_SCHEDULES` will switch to a different schedule everytime - a cycle is finished. - - - Setting `AFL_EXPAND_HAVOC_NOW` will start in the extended havoc mode that - includes costly mutations. afl-fuzz automatically enables this mode when - deemed useful otherwise. + - Setting `AFL_NO_FORKSRV` disables the forkserver optimization, reverting to + fork + execve() call for every tested input. This is useful mostly when + working with unruly libraries that create threads or do other crazy things + when initializing (before the instrumentation has a chance to run). - - Setting `AFL_PRELOAD` causes AFL++ to set `LD_PRELOAD` for the target binary - without disrupting the afl-fuzz process itself. This is useful, among other - things, for bootstrapping libdislocator.so. + Note that this setting inhibits some of the user-friendly diagnostics + normally done when starting up the forkserver and causes a pretty + significant performance drop. - - Setting `AFL_TARGET_ENV` causes AFL++ to set extra environment variables - for the target binary. Example: `AFL_TARGET_ENV="VAR1=1 VAR2='a b c'" afl-fuzz ... ` - This exists mostly for things like `LD_LIBRARY_PATH` but it would theoretically - allow fuzzing of AFL++ itself (with 'target' AFL++ using some AFL_ vars that - would disrupt work of 'fuzzer' AFL++). + - `AFL_NO_SNAPSHOT` will advice afl-fuzz not to use the snapshot feature if + the snapshot lkm is loaded. - - Setting `AFL_NO_UI` inhibits the UI altogether, and just periodically prints + - Setting `AFL_NO_UI` inhibits the UI altogether and just periodically prints some basic stats. This behavior is also automatically triggered when the output from afl-fuzz is redirected to a file or to a pipe. - - Setting `AFL_NO_COLOR` or `AFL_NO_COLOUR` will omit control sequences for - coloring console output when configured with USE_COLOR and not ALWAYS_COLORED. - - - Setting `AFL_FORCE_UI` will force painting the UI on the screen even if - no valid terminal was detected (for virtual consoles) + - In QEMU mode (-Q) and Frida mode (-O), `AFL_PATH` will be searched for + afl-qemu-trace and afl-frida-trace.so. - - If you are using persistent mode (you should, see [instrumentation/README.persistent_mode.md](instrumentation/README.persistent_mode.md)) - some targets keep inherent state due which a detected crash testcase does - not crash the target again when the testcase is given. To be able to still - re-trigger these crashes you can use the `AFL_PERSISTENT_RECORD` variable - with a value of how many previous fuzz cases to keep prio a crash. - if set to e.g. 10, then the 9 previous inputs are written to - out/default/crashes as RECORD:000000,cnt:000000 to RECORD:000000,cnt:000008 - and RECORD:000000,cnt:000009 being the crash case. - NOTE: This option needs to be enabled in config.h first! + - If you are using persistent mode (you should, see + [instrumentation/README.persistent_mode.md](../instrumentation/README.persistent_mode.md)), + some targets keep inherent state due which a detected crash test case does + not crash the target again when the test case is given. To be able to still + re-trigger these crashes, you can use the `AFL_PERSISTENT_RECORD` variable + with a value of how many previous fuzz cases to keep prio a crash. If set to + e.g., 10, then the 9 previous inputs are written to out/default/crashes as + RECORD:000000,cnt:000000 to RECORD:000000,cnt:000008 and + RECORD:000000,cnt:000009 being the crash case. NOTE: This option needs to be + enabled in config.h first! - - If afl-fuzz encounters an incorrect fuzzing setup during a fuzzing session - (not at startup), it will terminate. If you do not want this then you can - set `AFL_IGNORE_PROBLEMS`. - - - If you are Jakub, you may need `AFL_I_DONT_CARE_ABOUT_MISSING_CRASHES`. - Others need not apply, unless they also want to disable the - `/proc/sys/kernel/core_pattern` check. - - - Benchmarking only: `AFL_BENCH_JUST_ONE` causes the fuzzer to exit after - processing the first queue entry; and `AFL_BENCH_UNTIL_CRASH` causes it to - exit soon after the first crash is found. - - - Setting `AFL_DEBUG_CHILD` will not suppress the child output. - This lets you see all output of the child, making setup issues obvious. - For example, in an unicornafl harness, you might see python stacktraces. - You may also see other logs that way, indicating why the forkserver won't start. - Not pretty but good for debugging purposes. - Note that `AFL_DEBUG_CHILD_OUTPUT` is deprecated. + - Note that `AFL_POST_LIBRARY` is deprecated, use `AFL_CUSTOM_MUTATOR_LIBRARY` + instead. - - Setting `AFL_NO_CPU_RED` will not display very high cpu usages in red color. + - Setting `AFL_PRELOAD` causes AFL++ to set `LD_PRELOAD` for the target binary + without disrupting the afl-fuzz process itself. This is useful, among other + things, for bootstrapping libdislocator.so. - - Setting `AFL_AUTORESUME` will resume a fuzz run (same as providing `-i -`) - for an existing out folder, even if a different `-i` was provided. - Without this setting, afl-fuzz will refuse execution for a long-fuzzed out dir. + - In QEMU mode (-Q), setting `AFL_QEMU_CUSTOM_BIN` will cause afl-fuzz to skip + prepending `afl-qemu-trace` to your command line. Use this if you wish to + use a custom afl-qemu-trace or if you need to modify the afl-qemu-trace + arguments. - - Setting `AFL_MAX_DET_EXRAS` will change the threshold at what number of elements - in the `-x` dictionary and LTO autodict (combined) the probabilistic mode will - kick off. In probabilistic mode, not all dictionary entries will be used all - of the time for fuzzing mutations to not slow down fuzzing. - The default count is `200` elements. So for the 200 + 1st element, there is a - 1 in 201 chance, that one of the dictionary entries will not be used directly. + - `AFL_SHUFFLE_QUEUE` randomly reorders the input queue on startup. Requested + by some users for unorthodox parallelized fuzzing setups, but not advisable + otherwise. - - Setting `AFL_NO_FORKSRV` disables the forkserver optimization, reverting to - fork + execve() call for every tested input. This is useful mostly when - working with unruly libraries that create threads or do other crazy - things when initializing (before the instrumentation has a chance to run). + - When developing custom instrumentation on top of afl-fuzz, you can use + `AFL_SKIP_BIN_CHECK` to inhibit the checks for non-instrumented binaries and + shell scripts; and `AFL_DUMB_FORKSRV` in conjunction with the `-n` setting + to instruct afl-fuzz to still follow the fork server protocol without + expecting any instrumentation data in return. Note that this also turns off + auto map size detection. - Note that this setting inhibits some of the user-friendly diagnostics - normally done when starting up the forkserver and causes a pretty - significant performance drop. + - Setting `AFL_SKIP_CPUFREQ` skips the check for CPU scaling policy. This is + useful if you can't change the defaults (e.g., no root access to the system) + and are OK with some performance loss. + + - Setting `AFL_STATSD` enables StatsD metrics collection. By default, AFL++ + will send these metrics over UDP to 127.0.0.1:8125. The host and port are + configurable with `AFL_STATSD_HOST` and `AFL_STATSD_PORT` respectively. To + enable tags (banner and afl_version), you should provide + `AFL_STATSD_TAGS_FLAVOR` that matches your StatsD server (see + `AFL_STATSD_TAGS_FLAVOR`). + + - Setting `AFL_STATSD_TAGS_FLAVOR` to one of `dogstatsd`, `influxdb`, + `librato`, or `signalfx` allows you to add tags to your fuzzing instances. + This is especially useful when running multiple instances (`-M/-S` for + example). Applied tags are `banner` and `afl_version`. `banner` corresponds + to the name of the fuzzer provided through `-M/-S`. `afl_version` + corresponds to the currently running AFL++ version (e.g., `++3.0c`). Default + (empty/non present) will add no tags to the metrics. For more information, + see [rpc_statsd.md](rpc_statsd.md). + + - Setting `AFL_TARGET_ENV` causes AFL++ to set extra environment variables for + the target binary. Example: `AFL_TARGET_ENV="VAR1=1 VAR2='a b c'" afl-fuzz + ... `. This exists mostly for things like `LD_LIBRARY_PATH` but it would + theoretically allow fuzzing of AFL++ itself (with 'target' AFL++ using some + AFL_ vars that would disrupt work of 'fuzzer' AFL++). + + - `AFL_TESTCACHE_SIZE` allows you to override the size of `#define + TESTCASE_CACHE` in config.h. Recommended values are 50-250MB - or more if + your fuzzing finds a huge amount of paths for large inputs. + + - `AFL_TMPDIR` is used to write the `.cur_input` file to if it exists, and in + the normal output directory otherwise. You would use this to point to a + ramdisk/tmpfs. This increases the speed by a small value but also reduces + the stress on SSDs. - - Setting `AFL_STATSD` enables StatsD metrics collection. - By default AFL++ will send these metrics over UDP to 127.0.0.1:8125. - The host and port are configurable with `AFL_STATSD_HOST` and `AFL_STATSD_PORT` respectively. - To enable tags (banner and afl_version) you should provide `AFL_STATSD_TAGS_FLAVOR` that matches - your StatsD server (see `AFL_STATSD_TAGS_FLAVOR`) - - - Setting `AFL_STATSD_TAGS_FLAVOR` to one of `dogstatsd`, `librato`, `signalfx` or `influxdb` - allows you to add tags to your fuzzing instances. This is especially useful when running - multiple instances (`-M/-S` for example). Applied tags are `banner` and `afl_version`. - `banner` corresponds to the name of the fuzzer provided through `-M/-S`. - `afl_version` corresponds to the currently running AFL version (e.g `++3.0c`). - Default (empty/non present) will add no tags to the metrics. - See [rpc_statsd.md](rpc_statsd.md) for more information. - - - Setting `AFL_CRASH_EXITCODE` sets the exit code AFL treats as crash. - For example, if `AFL_CRASH_EXITCODE='-1'` is set, each input resulting - in an `-1` return code (i.e. `exit(-1)` got called), will be treated - as if a crash had ocurred. - This may be beneficial if you look for higher-level faulty conditions in which your - target still exits gracefully. + - Setting `AFL_TRY_AFFINITY` tries to attempt binding to a specific CPU core + on Linux systems, but will not terminate if that fails. - Outdated environment variables that are not supported anymore: - `AFL_DEFER_FORKSRV` - `AFL_PERSISTENT` + - `AFL_DEFER_FORKSRV` + - `AFL_PERSISTENT` ## 5) Settings for afl-qemu-trace The QEMU wrapper used to instrument binary-only code supports several settings: - - It is possible to set `AFL_INST_RATIO` to skip the instrumentation on some - of the basic blocks, which can be useful when dealing with very complex - binaries. - - - Setting `AFL_INST_LIBS` causes the translator to also instrument the code - inside any dynamically linked libraries (notably including glibc). - - Setting `AFL_COMPCOV_LEVEL` enables the CompareCoverage tracing of all cmp - and sub in x86 and x86_64 and memory comparions functions (e.g. strcmp, - memcmp, ...) when libcompcov is preloaded using `AFL_PRELOAD`. - More info at qemu_mode/libcompcov/README.md. + and sub in x86 and x86_64 and memory comparison functions (e.g., strcmp, + memcmp, ...) when libcompcov is preloaded using `AFL_PRELOAD`. More info at + [qemu_mode/libcompcov/README.md](../qemu_mode/libcompcov/README.md). + There are two levels at the moment, `AFL_COMPCOV_LEVEL=1` that instruments only comparisons with immediate values / read-only memory and - `AFL_COMPCOV_LEVEL=2` that instruments all the comparions. Level 2 is more + `AFL_COMPCOV_LEVEL=2` that instruments all the comparisons. Level 2 is more accurate but may need a larger shared memory. - - Setting `AFL_QEMU_COMPCOV` enables the CompareCoverage tracing of all - cmp and sub in x86 and x86_64. - This is an alias of `AFL_COMPCOV_LEVEL=1` when `AFL_COMPCOV_LEVEL` is - not specified. + - `AFL_DEBUG` will print the found entry point for the binary to stderr. Use + this if you are unsure if the entry point might be wrong - but use it + directly, e.g., `afl-qemu-trace ./program`. - - The underlying QEMU binary will recognize any standard "user space - emulation" variables (e.g., `QEMU_STACK_SIZE`), but there should be no - reason to touch them. + - `AFL_ENTRYPOINT` allows you to specify a specific entry point into the + binary (this can be very good for the performance!). The entry point is + specified as hex address, e.g., `0x4004110`. Note that the address must be + the address of a basic block. + + - Setting `AFL_INST_LIBS` causes the translator to also instrument the code + inside any dynamically linked libraries (notably including glibc). + + - It is possible to set `AFL_INST_RATIO` to skip the instrumentation on some + of the basic blocks, which can be useful when dealing with very complex + binaries. - - `AFL_DEBUG` will print the found entrypoint for the binary to stderr. - Use this if you are unsure if the entrypoint might be wrong - but - use it directly, e.g. `afl-qemu-trace ./program` + - Setting `AFL_QEMU_COMPCOV` enables the CompareCoverage tracing of all cmp + and sub in x86 and x86_64. This is an alias of `AFL_COMPCOV_LEVEL=1` when + `AFL_COMPCOV_LEVEL` is not specified. - - `AFL_ENTRYPOINT` allows you to specify a specific entrypoint into the - binary (this can be very good for the performance!). - The entrypoint is specified as hex address, e.g. `0x4004110` - Note that the address must be the address of a basic block. + - With `AFL_QEMU_FORCE_DFL`, you force QEMU to ignore the registered signal + handlers of the target. - - When the target is i386/x86_64 you can specify the address of the function + - When the target is i386/x86_64, you can specify the address of the function that has to be the body of the persistent loop using `AFL_QEMU_PERSISTENT_ADDR=start addr`. - - Another modality to execute the persistent loop is to specify also the - `AFL_QEMU_PERSISTENT_RET=end addr` env variable. - With this variable assigned, instead of patching the return address, the - specified instruction is transformed to a jump towards `start addr`. + - With `AFL_QEMU_PERSISTENT_GPR=1`, QEMU will save the original value of + general purpose registers and restore them in each persistent cycle. - - `AFL_QEMU_PERSISTENT_GPR=1` QEMU will save the original value of general - purpose registers and restore them in each persistent cycle. + - Another modality to execute the persistent loop is to specify also the + `AFL_QEMU_PERSISTENT_RET=end addr` environment variable. With this variable + assigned, instead of patching the return address, the specified instruction + is transformed to a jump towards `start addr`. - - With `AFL_QEMU_PERSISTENT_RETADDR_OFFSET` you can specify the offset from the - stack pointer in which QEMU can find the return address when `start addr` is - hit. + - With `AFL_QEMU_PERSISTENT_RETADDR_OFFSET`, you can specify the offset from + the stack pointer in which QEMU can find the return address when `start + addr` is hit. - - With `AFL_USE_QASAN` you can enable QEMU AddressSanitizer for dynamically + - With `AFL_USE_QASAN`, you can enable QEMU AddressSanitizer for dynamically linked binaries. - - With `AFL_QEMU_FORCE_DFL` you force QEMU to ignore the registered signal - handlers of the target. + - The underlying QEMU binary will recognize any standard "user space + emulation" variables (e.g., `QEMU_STACK_SIZE`), but there should be no + reason to touch them. -## 6) Settings for afl-cmin +## 7) Settings for afl-frida-trace + +The FRIDA wrapper used to instrument binary-only code supports many of the same +options as `afl-qemu-trace`, but also has a number of additional advanced +options. These are listed in brief below (see +[frida_mode/README.md](../frida_mode/README.md) for more details). These +settings are provided for compatibility with QEMU mode, the preferred way to +configure FRIDA mode is through its [scripting](../frida_mode/Scripting.md) +support. + +* `AFL_FRIDA_DEBUG_MAPS` - See `AFL_QEMU_DEBUG_MAPS` +* `AFL_FRIDA_DRIVER_NO_HOOK` - See `AFL_QEMU_DRIVER_NO_HOOK`. When using the + QEMU driver to provide a `main` loop for a user provided + `LLVMFuzzerTestOneInput`, this option configures the driver to read input from + `stdin` rather than using in-memory test cases. +* `AFL_FRIDA_EXCLUDE_RANGES` - See `AFL_QEMU_EXCLUDE_RANGES` +* `AFL_FRIDA_INST_COVERAGE_FILE` - File to write DynamoRio format coverage + information (e.g., to be loaded within IDA lighthouse). +* `AFL_FRIDA_INST_DEBUG_FILE` - File to write raw assembly of original blocks + and their instrumented counterparts during block compilation. +* `AFL_FRIDA_INST_JIT` - Enable the instrumentation of Just-In-Time compiled + code. Code is considered to be JIT if the executable segment is not backed by + a file. +* `AFL_FRIDA_INST_NO_OPTIMIZE` - Don't use optimized inline assembly coverage + instrumentation (the default where available). Required to use + `AFL_FRIDA_INST_TRACE`. +* `AFL_FRIDA_INST_NO_BACKPATCH` - Disable backpatching. At the end of executing + each block, control will return to FRIDA to identify the next block to + execute. +* `AFL_FRIDA_INST_NO_PREFETCH` - Disable prefetching. By default, the child will + report instrumented blocks back to the parent so that it can also instrument + them and they be inherited by the next child on fork, implies + `AFL_FRIDA_INST_NO_PREFETCH_BACKPATCH`. +* `AFL_FRIDA_INST_NO_PREFETCH_BACKPATCH` - Disable prefetching of stalker + backpatching information. By default, the child will report applied + backpatches to the parent so that they can be applied and then be inherited by + the next child on fork. +* `AFL_FRIDA_INST_RANGES` - See `AFL_QEMU_INST_RANGES` +* `AFL_FRIDA_INST_SEED` - Sets the initial seed for the hash function used to + generate block (and hence edge) IDs. Setting this to a constant value may be + useful for debugging purposes, e.g., investigating unstable edges. +* `AFL_FRIDA_INST_TRACE` - Log to stdout the address of executed blocks, implies + `AFL_FRIDA_INST_NO_OPTIMIZE`. +* `AFL_FRIDA_INST_TRACE_UNIQUE` - As per `AFL_FRIDA_INST_TRACE`, but each edge + is logged only once, requires `AFL_FRIDA_INST_NO_OPTIMIZE`. +* `AFL_FRIDA_INST_UNSTABLE_COVERAGE_FILE` - File to write DynamoRio format + coverage information for unstable edges (e.g., to be loaded within IDA + lighthouse). +* `AFL_FRIDA_JS_SCRIPT` - Set the script to be loaded by the FRIDA scripting + engine. See [frida_mode/Scripting.md](../frida_mode/Scripting.md) for details. +* `AFL_FRIDA_OUTPUT_STDOUT` - Redirect the standard output of the target + application to the named file (supersedes the setting of `AFL_DEBUG_CHILD`) +* `AFL_FRIDA_OUTPUT_STDERR` - Redirect the standard error of the target + application to the named file (supersedes the setting of `AFL_DEBUG_CHILD`) +* `AFL_FRIDA_PERSISTENT_ADDR` - See `AFL_QEMU_PERSISTENT_ADDR` +* `AFL_FRIDA_PERSISTENT_CNT` - See `AFL_QEMU_PERSISTENT_CNT` +* `AFL_FRIDA_PERSISTENT_DEBUG` - Insert a Breakpoint into the instrumented code + at `AFL_FRIDA_PERSISTENT_HOOK` and `AFL_FRIDA_PERSISTENT_RET` to allow the + user to detect issues in the persistent loop using a debugger. +* `AFL_FRIDA_PERSISTENT_HOOK` - See `AFL_QEMU_PERSISTENT_HOOK` +* `AFL_FRIDA_PERSISTENT_RET` - See `AFL_QEMU_PERSISTENT_RET` +* `AFL_FRIDA_SECCOMP_FILE` - Write a log of any syscalls made by the target to + the specified file. +* `AFL_FRIDA_STALKER_ADJACENT_BLOCKS` - Configure the number of adjacent blocks + to fetch when generating instrumented code. By fetching blocks in the same + order they appear in the original program, rather than the order of execution + should help reduce locallity and adjacency. This includes allowing us to + vector between adjancent blocks using a NOP slide rather than an immediate + branch. +* `AFL_FRIDA_STALKER_IC_ENTRIES` - Configure the number of inline cache entries + stored along-side branch instructions which provide a cache to avoid having to + call back into FRIDA to find the next block. Default is 32. +* `AFL_FRIDA_STATS_FILE` - Write statistics information about the code being + instrumented to the given file name. The statistics are written only for the + child process when new block is instrumented (when the + `AFL_FRIDA_STATS_INTERVAL` has expired). Note that just because a new path is + found does not mean a new block needs to be compiled. It could be that the + existing blocks instrumented have been executed in a different order. +* `AFL_FRIDA_STATS_INTERVAL` - The maximum frequency to output statistics + information. Stats will be written whenever they are updated if the given + interval has elapsed since last time they were written. +* `AFL_FRIDA_TRACEABLE` - Set the child process to be traceable by any process + to aid debugging and overcome the restrictions imposed by YAMA. Supported on + Linux only. Permits a non-root user to use `gcore` or similar to collect a + core dump of the instrumented target. Note that in order to capture the core + dump you must set a sufficient timeout (using `-t`) to avoid `afl-fuzz` + killing the process whilst it is being dumped. + +## 8) Settings for afl-cmin The corpus minimization script offers very little customization: - - Setting `AFL_PATH` offers a way to specify the location of afl-showmap - and afl-qemu-trace (the latter only in `-Q` mode). + - `AFL_ALLOW_TMP` permits this and some other scripts to run in /tmp. This is + a modest security risk on multi-user systems with rogue users, but should be + safe on dedicated fuzzing boxes. - `AFL_KEEP_TRACES` makes the tool keep traces and other metadata used for minimization and normally deleted at exit. The files can be found in the `<out_dir>/.traces/` directory. - - `AFL_ALLOW_TMP` permits this and some other scripts to run in /tmp. This is - a modest security risk on multi-user systems with rogue users, but should - be safe on dedicated fuzzing boxes. + - Setting `AFL_PATH` offers a way to specify the location of afl-showmap and + afl-qemu-trace (the latter only in `-Q` mode). - `AFL_PRINT_FILENAMES` prints each filename to stdout, as it gets processed. - This can help when embedding `afl-cmin` or `afl-showmap` in other scripts scripting. + This can help when embedding `afl-cmin` or `afl-showmap` in other scripts. -## 7) Settings for afl-tmin +## 9) Settings for afl-tmin Virtually nothing to play with. Well, in QEMU mode (`-Q`), `AFL_PATH` will be searched for afl-qemu-trace. In addition to this, `TMPDIR` may be used if a @@ -587,77 +696,81 @@ to match when minimizing crashes. This will make minimization less useful, but may prevent the tool from "jumping" from one crashing condition to another in very buggy software. You probably want to combine it with the `-e` flag. -## 8) Settings for afl-analyze +## 10) Settings for afl-analyze You can set `AFL_ANALYZE_HEX` to get file offsets printed as hexadecimal instead of decimal. -## 9) Settings for libdislocator +## 11) Settings for libdislocator -The library honors these environmental variables: +The library honors these environment variables: - - `AFL_LD_LIMIT_MB` caps the size of the maximum heap usage permitted by the - library, in megabytes. The default value is 1 GB. Once this is exceeded, - allocations will return NULL. + - `AFL_ALIGNED_ALLOC=1` will force the alignment of the allocation size to + `max_align_t` to be compliant with the C standard. - `AFL_LD_HARD_FAIL` alters the behavior by calling `abort()` on excessive allocations, thus causing what AFL++ would perceive as a crash. Useful for programs that are supposed to maintain a specific memory footprint. - - `AFL_LD_VERBOSE` causes the library to output some diagnostic messages - that may be useful for pinpointing the cause of any observed issues. + - `AFL_LD_LIMIT_MB` caps the size of the maximum heap usage permitted by the + library, in megabytes. The default value is 1 GB. Once this is exceeded, + allocations will return NULL. - - `AFL_LD_NO_CALLOC_OVER` inhibits `abort()` on `calloc()` overflows. Most - of the common allocators check for that internally and return NULL, so - it's a security risk only in more exotic setups. + - `AFL_LD_NO_CALLOC_OVER` inhibits `abort()` on `calloc()` overflows. Most of + the common allocators check for that internally and return NULL, so it's a + security risk only in more exotic setups. - - `AFL_ALIGNED_ALLOC=1` will force the alignment of the allocation size to - `max_align_t` to be compliant with the C standard. + - `AFL_LD_VERBOSE` causes the library to output some diagnostic messages that + may be useful for pinpointing the cause of any observed issues. -## 10) Settings for libtokencap +## 11) Settings for libtokencap This library accepts `AFL_TOKEN_FILE` to indicate the location to which the discovered tokens should be written. -## 11) Third-party variables set by afl-fuzz & other tools +## 12) Third-party variables set by afl-fuzz & other tools Several variables are not directly interpreted by afl-fuzz, but are set to optimal values if not already present in the environment: - - By default, `LD_BIND_NOW` is set to speed up fuzzing by forcing the - linker to do all the work before the fork server kicks in. You can - override this by setting `LD_BIND_LAZY` beforehand, but it is almost - certainly pointless. - - By default, `ASAN_OPTIONS` are set to (among others): -``` + + ``` abort_on_error=1 detect_leaks=0 malloc_context_size=0 symbolize=0 allocator_may_return_null=1 -``` - If you want to set your own options, be sure to include `abort_on_error=1` - - otherwise, the fuzzer will not be able to detect crashes in the tested - app. Similarly, include `symbolize=0`, since without it, AFL++ may have + ``` + + If you want to set your own options, be sure to include `abort_on_error=1` - + otherwise, the fuzzer will not be able to detect crashes in the tested app. + Similarly, include `symbolize=0`, since without it, AFL++ may have difficulty telling crashes and hangs apart. + - Similarly, the default `LSAN_OPTIONS` are set to: + + ``` + exit_code=23 + fast_unwind_on_malloc=0 + symbolize=0 + print_suppressions=0 + ``` + + Be sure to include the first ones for LSAN and MSAN when customizing + anything, since some MSAN and LSAN versions don't call `abort()` on error, + and we need a way to detect faults. + - In the same vein, by default, `MSAN_OPTIONS` are set to: -``` + + ``` exit_code=86 (required for legacy reasons) abort_on_error=1 symbolize=0 msan_track_origins=0 allocator_may_return_null=1 -``` - - Similarly, the default `LSAN_OPTIONS` are set to: -``` - exit_code=23 - fast_unwind_on_malloc=0 - symbolize=0 - print_suppressions=0 -``` - Be sure to include the first ones for LSAN and MSAN when customizing - anything, since some MSAN and LSAN versions don't call `abort()` on - error, and we need a way to detect faults. + ``` + - By default, `LD_BIND_NOW` is set to speed up fuzzing by forcing the linker + to do all the work before the fork server kicks in. You can override this by + setting `LD_BIND_LAZY` beforehand, but it is almost certainly pointless. diff --git a/docs/features.md b/docs/features.md new file mode 100644 index 00000000..431d9eb1 --- /dev/null +++ b/docs/features.md @@ -0,0 +1,61 @@ +# Important features of AFL++ + +AFL++ supports llvm from 3.8 up to version 12, very fast binary fuzzing with +QEMU 5.1 with laf-intel and redqueen, FRIDA mode, unicorn mode, gcc plugin, full +*BSD, Mac OS, Solaris and Android support and much, much, much more. + +| Feature/Instrumentation | afl-gcc | llvm | gcc_plugin | FRIDA mode(9) | QEMU mode(10) |unicorn_mode(10) |coresight_mode(11)| +| -------------------------|:-------:|:---------:|:----------:|:----------------:|:----------------:|:----------------:|:----------------:| +| Threadsafe counters | | x(3) | | | | | | +| NeverZero | x86[_64]| x(1) | x | x | x | x | | +| Persistent Mode | | x | x | x86[_64]/arm64 | x86[_64]/arm[64] | x | | +| LAF-Intel / CompCov | | x | | | x86[_64]/arm[64] | x86[_64]/arm[64] | | +| CmpLog | | x | | x86[_64]/arm64 | x86[_64]/arm[64] | | | +| Selective Instrumentation| | x | x | x | x | | | +| Non-Colliding Coverage | | x(4) | | | (x)(5) | | | +| Ngram prev_loc Coverage | | x(6) | | | | | | +| Context Coverage | | x(6) | | | | | | +| Auto Dictionary | | x(7) | | | | | | +| Snapshot LKM Support | | (x)(8) | (x)(8) | | (x)(5) | | | +| Shared Memory Test cases | | x | x | x86[_64]/arm64 | x | x | | + +1. default for LLVM >= 9.0, environment variable for older version due an + efficiency bug in previous llvm versions +2. GCC creates non-performant code, hence it is disabled in gcc_plugin +3. with `AFL_LLVM_THREADSAFE_INST`, disables NeverZero +4. with pcguard mode and LTO mode for LLVM 11 and newer +5. upcoming, development in the branch +6. not compatible with LTO instrumentation and needs at least LLVM v4.1 +7. automatic in LTO mode with LLVM 11 and newer, an extra pass for all LLVM + versions that write to a file to use with afl-fuzz' `-x` +8. the snapshot LKM is currently unmaintained due to too many kernel changes + coming too fast :-( +9. FRIDA mode is supported on Linux and MacOS for Intel and ARM +10. QEMU/Unicorn is only supported on Linux +11. Coresight mode is only available on AARCH64 Linux with a CPU with Coresight + extension + +Among others, the following features and patches have been integrated: + +* NeverZero patch for afl-gcc, instrumentation, QEMU mode and unicorn_mode which + prevents a wrapping map value to zero, increases coverage +* Persistent mode, deferred forkserver and in-memory fuzzing for QEMU mode +* Unicorn mode which allows fuzzing of binaries from completely different + platforms (integration provided by domenukk) +* The new CmpLog instrumentation for LLVM and QEMU inspired by + [Redqueen](https://www.syssec.ruhr-uni-bochum.de/media/emma/veroeffentlichungen/2018/12/17/NDSS19-Redqueen.pdf) +* Win32 PE binary-only fuzzing with QEMU and Wine +* AFLfast's power schedules by Marcel Böhme: + [https://github.com/mboehme/aflfast](https://github.com/mboehme/aflfast) +* The MOpt mutator: + [https://github.com/puppet-meteor/MOpt-AFL](https://github.com/puppet-meteor/MOpt-AFL) +* LLVM mode Ngram coverage by Adrian Herrera + [https://github.com/adrianherrera/afl-ngram-pass](https://github.com/adrianherrera/afl-ngram-pass) +* LAF-Intel/CompCov support for instrumentation, QEMU mode and unicorn_mode + (with enhanced capabilities) +* Radamsa and honggfuzz mutators (as custom mutators). +* QBDI mode to fuzz android native libraries via Quarkslab's + [QBDI](https://github.com/QBDI/QBDI) framework +* Frida and ptrace mode to fuzz binary-only libraries, etc. + +So all in all this is the best-of AFL that is out there :-) \ No newline at end of file diff --git a/docs/fuzzing_binary-only_targets.md b/docs/fuzzing_binary-only_targets.md new file mode 100644 index 00000000..5434a22c --- /dev/null +++ b/docs/fuzzing_binary-only_targets.md @@ -0,0 +1,296 @@ +# Fuzzing binary-only targets + +AFL++, libfuzzer, and other fuzzers are great if you have the source code of the +target. This allows for very fast and coverage guided fuzzing. + +However, if there is only the binary program and no source code available, then +standard `afl-fuzz -n` (non-instrumented mode) is not effective. + +For fast, on-the-fly instrumentation of black-box binaries, AFL++ still offers +various support. The following is a description of how these binaries can be +fuzzed with AFL++. + +## TL;DR: + +QEMU mode in persistent mode is the fastest - if the stability is high enough. +Otherwise, try RetroWrite, Dyninst, and if these fail, too, then try standard +QEMU mode with `AFL_ENTRYPOINT` to where you need it. + +If your target is a library, then use FRIDA mode. + +If your target is non-linux, then use unicorn_mode. + +## Fuzzing binary-only targets with AFL++ + +### QEMU mode + +QEMU mode is the "native" solution to the program. It is available in the +./qemu_mode/ directory and, once compiled, it can be accessed by the afl-fuzz -Q +command line option. It is the easiest to use alternative and even works for +cross-platform binaries. + +For linux programs and its libraries, this is accomplished with a version of +QEMU running in the lesser-known "user space emulation" mode. QEMU is a project +separate from AFL++, but you can conveniently build the feature by doing: + +```shell +cd qemu_mode +./build_qemu_support.sh +``` + +The following setup to use QEMU mode is recommended: + +* run 1 afl-fuzz -Q instance with CMPLOG (`-c 0` + `AFL_COMPCOV_LEVEL=2`) +* run 1 afl-fuzz -Q instance with QASAN (`AFL_USE_QASAN=1`) +* run 1 afl-fuzz -Q instance with LAF (`AFL_PRELOAD=libcmpcov.so` + + `AFL_COMPCOV_LEVEL=2`), alternatively you can use FRIDA mode, just switch `-Q` + with `-O` and remove the LAF instance + +Then run as many instances as you have cores left with either -Q mode or - even +better - use a binary rewriter like Dyninst, RetroWrite, ZAFL, etc. + +If [afl-dyninst](https://github.com/vanhauser-thc/afl-dyninst) works for your +binary, then you can use afl-fuzz normally and it will have twice the speed +compared to QEMU mode (but slower than QEMU persistent mode). Note that several +other binary rewriters exist, all with their advantages and caveats. + +The speed decrease of QEMU mode is at about 50%. However, various options exist +to increase the speed: +- using AFL_ENTRYPOINT to move the forkserver entry to a later basic block in + the binary (+5-10% speed) +- using persistent mode + [qemu_mode/README.persistent.md](../qemu_mode/README.persistent.md) this will + result in a 150-300% overall speed increase - so 3-8x the original QEMU mode + speed! +- using AFL_CODE_START/AFL_CODE_END to only instrument specific parts + +For additional instructions and caveats, see +[qemu_mode/README.md](../qemu_mode/README.md). If possible, you should use the +persistent mode, see +[qemu_mode/README.persistent.md](../qemu_mode/README.persistent.md). The mode is +approximately 2-5x slower than compile-time instrumentation, and is less +conducive to parallelization. + +Note that there is also honggfuzz: +[https://github.com/google/honggfuzz](https://github.com/google/honggfuzz) which +now has a QEMU mode, but its performance is just 1.5% ... + +If you like to code a customized fuzzer without much work, we highly recommend +to check out our sister project libafl which supports QEMU, too: +[https://github.com/AFLplusplus/LibAFL](https://github.com/AFLplusplus/LibAFL) + +### WINE+QEMU + +Wine mode can run Win32 PE binaries with the QEMU instrumentation. It needs +Wine, python3, and the pefile python package installed. + +It is included in AFL++. + +For more information, see +[qemu_mode/README.wine.md](../qemu_mode/README.wine.md). + +### FRIDA mode + +In FRIDA mode, you can fuzz binary-only targets as easily as with QEMU mode. +FRIDA mode is sometimes faster and sometimes slower than QEMU mode. It is also +newer, lacks COMPCOV, and has the advantage that it works on MacOS (both intel +and M1). + +To build FRIDA mode: + +```shell +cd frida_mode +make +``` + +For additional instructions and caveats, see +[frida_mode/README.md](../frida_mode/README.md). + +If possible, you should use the persistent mode, see +[instrumentation/README.persistent_mode.md](../instrumentation/README.persistent_mode.md). +The mode is approximately 2-5x slower than compile-time instrumentation, and is +less conducive to parallelization. But for binary-only fuzzing, it gives a huge +speed improvement if it is possible to use. + +If you want to fuzz a binary-only library, then you can fuzz it with frida-gum +via frida_mode/. You will have to write a harness to call the target function in +the library, use afl-frida.c as a template. + +You can also perform remote fuzzing with frida, e.g., if you want to fuzz on +iPhone or Android devices, for this you can use +[https://github.com/ttdennis/fpicker/](https://github.com/ttdennis/fpicker/) as +an intermediate that uses AFL++ for fuzzing. + +If you like to code a customized fuzzer without much work, we highly recommend +to check out our sister project libafl which supports Frida, too: +[https://github.com/AFLplusplus/LibAFL](https://github.com/AFLplusplus/LibAFL). +Working examples already exist :-) + +### Unicorn + +Unicorn is a fork of QEMU. The instrumentation is, therefore, very similar. In +contrast to QEMU, Unicorn does not offer a full system or even userland +emulation. Runtime environment and/or loaders have to be written from scratch, +if needed. On top, block chaining has been removed. This means the speed boost +introduced in the patched QEMU Mode of AFL++ cannot be ported over to Unicorn. + +For non-Linux binaries, you can use AFL++'s unicorn_mode which can emulate +anything you want - for the price of speed and user written scripts. + +To build unicorn_mode: + +```shell +cd unicorn_mode +./build_unicorn_support.sh +``` + +For further information, check out +[unicorn_mode/README.md](../unicorn_mode/README.md). + +### Shared libraries + +If the goal is to fuzz a dynamic library, then there are two options available. +For both, you need to write a small harness that loads and calls the library. +Then you fuzz this with either FRIDA mode or QEMU mode and either use +`AFL_INST_LIBS=1` or `AFL_QEMU/FRIDA_INST_RANGES`. + +Another, less precise and slower option is to fuzz it with utils/afl_untracer/ +and use afl-untracer.c as a template. It is slower than FRIDA mode. + +For more information, see +[utils/afl_untracer/README.md](../utils/afl_untracer/README.md). + +### Coresight + +Coresight is ARM's answer to Intel's PT. With AFL++ v3.15, there is a coresight +tracer implementation available in `coresight_mode/` which is faster than QEMU, +however, cannot run in parallel. Currently, only one process can be traced, it +is WIP. + +Fore more information, see +[coresight_mode/README.md](../coresight_mode/README.md). + +## Binary rewriters + +An alternative solution are binary rewriters. They are faster than the solutions +native to AFL++ but don't always work. + +### ZAFL + +ZAFL is a static rewriting platform supporting x86-64 C/C++, +stripped/unstripped, and PIE/non-PIE binaries. Beyond conventional +instrumentation, ZAFL's API enables transformation passes (e.g., laf-Intel, +context sensitivity, InsTrim, etc.). + +Its baseline instrumentation speed typically averages 90-95% of +afl-clang-fast's. + +[https://git.zephyr-software.com/opensrc/zafl](https://git.zephyr-software.com/opensrc/zafl) + +### RetroWrite + +If you have an x86/x86_64 binary that still has its symbols, is compiled with +position independent code (PIC/PIE), and does not use most of the C++ features, +then the RetroWrite solution might be for you. It decompiles to ASM files which +can then be instrumented with afl-gcc. + +It is at about 80-85% performance. + +[https://github.com/HexHive/retrowrite](https://github.com/HexHive/retrowrite) + +### Dyninst + +Dyninst is a binary instrumentation framework similar to Pintool and DynamoRIO. +However, whereas Pintool and DynamoRIO work at runtime, Dyninst instruments the +target at load time and then let it run - or save the binary with the changes. +This is great for some things, e.g., fuzzing, and not so effective for others, +e.g., malware analysis. + +So, what you can do with Dyninst is taking every basic block and putting AFL++'s +instrumentation code in there - and then save the binary. Afterwards, just fuzz +the newly saved target binary with afl-fuzz. Sounds great? It is. The issue +though - it is a non-trivial problem to insert instructions, which change +addresses in the process space, so that everything is still working afterwards. +Hence, more often than not binaries crash when they are run. + +The speed decrease is about 15-35%, depending on the optimization options used +with afl-dyninst. + +[https://github.com/vanhauser-thc/afl-dyninst](https://github.com/vanhauser-thc/afl-dyninst) + +### Mcsema + +Theoretically, you can also decompile to llvm IR with mcsema, and then use +llvm_mode to instrument the binary. Good luck with that. + +[https://github.com/lifting-bits/mcsema](https://github.com/lifting-bits/mcsema) + +## Binary tracers + +### Pintool & DynamoRIO + +Pintool and DynamoRIO are dynamic instrumentation engines. They can be used for +getting basic block information at runtime. Pintool is only available for Intel +x32/x64 on Linux, Mac OS, and Windows, whereas DynamoRIO is additionally +available for ARM and AARCH64. DynamoRIO is also 10x faster than Pintool. + +The big issue with DynamoRIO (and therefore Pintool, too) is speed. DynamoRIO +has a speed decrease of 98-99%, Pintool has a speed decrease of 99.5%. + +Hence, DynamoRIO is the option to go for if everything else fails and Pintool +only if DynamoRIO fails, too. + +DynamoRIO solutions: +* [https://github.com/vanhauser-thc/afl-dynamorio](https://github.com/vanhauser-thc/afl-dynamorio) +* [https://github.com/mxmssh/drAFL](https://github.com/mxmssh/drAFL) +* [https://github.com/googleprojectzero/winafl/](https://github.com/googleprojectzero/winafl/) + <= very good but windows only + +Pintool solutions: +* [https://github.com/vanhauser-thc/afl-pin](https://github.com/vanhauser-thc/afl-pin) +* [https://github.com/mothran/aflpin](https://github.com/mothran/aflpin) +* [https://github.com/spinpx/afl_pin_mode](https://github.com/spinpx/afl_pin_mode) + <= only old Pintool version supported + +### Intel PT + +If you have a newer Intel CPU, you can make use of Intel's processor trace. The +big issue with Intel's PT is the small buffer size and the complex encoding of +the debug information collected through PT. This makes the decoding very CPU +intensive and hence slow. As a result, the overall speed decrease is about +70-90% (depending on the implementation and other factors). + +There are two AFL intel-pt implementations: + +1. [https://github.com/junxzm1990/afl-pt](https://github.com/junxzm1990/afl-pt) + => This needs Ubuntu 14.04.05 without any updates and the 4.4 kernel. + +2. [https://github.com/hunter-ht-2018/ptfuzzer](https://github.com/hunter-ht-2018/ptfuzzer) + => This needs a 4.14 or 4.15 kernel. The "nopti" kernel boot option must be + used. This one is faster than the other. + +Note that there is also honggfuzz: +[https://github.com/google/honggfuzz](https://github.com/google/honggfuzz). But +its IPT performance is just 6%! + +## Non-AFL++ solutions + +There are many binary-only fuzzing frameworks. Some are great for CTFs but don't +work with large binaries, others are very slow but have good path discovery, +some are very hard to set-up... + +* Jackalope: + [https://github.com/googleprojectzero/Jackalope](https://github.com/googleprojectzero/Jackalope) +* Manticore: + [https://github.com/trailofbits/manticore](https://github.com/trailofbits/manticore) +* QSYM: + [https://github.com/sslab-gatech/qsym](https://github.com/sslab-gatech/qsym) +* S2E: [https://github.com/S2E](https://github.com/S2E) +* TinyInst: + [https://github.com/googleprojectzero/TinyInst](https://github.com/googleprojectzero/TinyInst) + (Mac/Windows only) +* ... please send me any missing that are good + +## Closing words + +That's it! News, corrections, updates? Send an email to vh@thc.org. \ No newline at end of file diff --git a/docs/fuzzing_in_depth.md b/docs/fuzzing_in_depth.md new file mode 100644 index 00000000..aaceb600 --- /dev/null +++ b/docs/fuzzing_in_depth.md @@ -0,0 +1,861 @@ +# Fuzzing with AFL++ + +The following describes how to fuzz with a target if source code is available. +If you have a binary-only target, go to +[fuzzing_binary-only_targets.md](fuzzing_binary-only_targets.md). + +Fuzzing source code is a three-step process: + +1. Compile the target with a special compiler that prepares the target to be + fuzzed efficiently. This step is called "instrumenting a target". +2. Prepare the fuzzing by selecting and optimizing the input corpus for the + target. +3. Perform the fuzzing of the target by randomly mutating input and assessing if + a generated input was processed in a new path in the target binary. + +## 0. Common sense risks + +Please keep in mind that, similarly to many other computationally-intensive +tasks, fuzzing may put a strain on your hardware and on the OS. In particular: + +- Your CPU will run hot and will need adequate cooling. In most cases, if + cooling is insufficient or stops working properly, CPU speeds will be + automatically throttled. That said, especially when fuzzing on less suitable + hardware (laptops, smartphones, etc.), it's not entirely impossible for + something to blow up. + +- Targeted programs may end up erratically grabbing gigabytes of memory or + filling up disk space with junk files. AFL++ tries to enforce basic memory + limits, but can't prevent each and every possible mishap. The bottom line is + that you shouldn't be fuzzing on systems where the prospect of data loss is + not an acceptable risk. + +- Fuzzing involves billions of reads and writes to the filesystem. On modern + systems, this will be usually heavily cached, resulting in fairly modest + "physical" I/O - but there are many factors that may alter this equation. It + is your responsibility to monitor for potential trouble; with very heavy I/O, + the lifespan of many HDDs and SSDs may be reduced. + + A good way to monitor disk I/O on Linux is the `iostat` command: + + ```shell + $ iostat -d 3 -x -k [...optional disk ID...] + ``` + + Using the `AFL_TMPDIR` environment variable and a RAM-disk, you can have the + heavy writing done in RAM to prevent the aforementioned wear and tear. For + example, the following line will run a Docker container with all this preset: + + ```shell + # docker run -ti --mount type=tmpfs,destination=/ramdisk -e AFL_TMPDIR=/ramdisk aflplusplus/aflplusplus + ``` + +## 1. Instrumenting the target + +### a) Selecting the best AFL++ compiler for instrumenting the target + +AFL++ comes with a central compiler `afl-cc` that incorporates various different +kinds of compiler targets and and instrumentation options. The following +evaluation flow will help you to select the best possible. + +It is highly recommended to have the newest llvm version possible installed, +anything below 9 is not recommended. + +``` ++--------------------------------+ +| clang/clang++ 11+ is available | --> use LTO mode (afl-clang-lto/afl-clang-lto++) ++--------------------------------+ see [instrumentation/README.lto.md](instrumentation/README.lto.md) + | + | if not, or if the target fails with LTO afl-clang-lto/++ + | + v ++---------------------------------+ +| clang/clang++ 3.8+ is available | --> use LLVM mode (afl-clang-fast/afl-clang-fast++) ++---------------------------------+ see [instrumentation/README.llvm.md](instrumentation/README.llvm.md) + | + | if not, or if the target fails with LLVM afl-clang-fast/++ + | + v + +--------------------------------+ + | gcc 5+ is available | -> use GCC_PLUGIN mode (afl-gcc-fast/afl-g++-fast) + +--------------------------------+ see [instrumentation/README.gcc_plugin.md](instrumentation/README.gcc_plugin.md) and + [instrumentation/README.instrument_list.md](instrumentation/README.instrument_list.md) + | + | if not, or if you do not have a gcc with plugin support + | + v + use GCC mode (afl-gcc/afl-g++) (or afl-clang/afl-clang++ for clang) +``` + +Clickable README links for the chosen compiler: + +* [LTO mode - afl-clang-lto](../instrumentation/README.lto.md) +* [LLVM mode - afl-clang-fast](../instrumentation/README.llvm.md) +* [GCC_PLUGIN mode - afl-gcc-fast](../instrumentation/README.gcc_plugin.md) +* GCC/CLANG modes (afl-gcc/afl-clang) have no README as they have no own + features + +You can select the mode for the afl-cc compiler by: +1. use a symlink to afl-cc: afl-gcc, afl-g++, afl-clang, afl-clang++, + afl-clang-fast, afl-clang-fast++, afl-clang-lto, afl-clang-lto++, + afl-gcc-fast, afl-g++-fast (recommended!) +2. using the environment variable AFL_CC_COMPILER with MODE +3. passing --afl-MODE command line options to the compiler via + CFLAGS/CXXFLAGS/CPPFLAGS + +MODE can be one of: LTO (afl-clang-lto*), LLVM (afl-clang-fast*), GCC_PLUGIN +(afl-g*-fast) or GCC (afl-gcc/afl-g++) or CLANG(afl-clang/afl-clang++). + +Because no AFL++ specific command-line options are accepted (beside the +--afl-MODE command), the compile-time tools make fairly broad use of environment +variables, which can be listed with `afl-cc -hh` or by reading +[env_variables.md](env_variables.md). + +### b) Selecting instrumentation options + +The following options are available when you instrument with LTO mode +(afl-clang-fast/afl-clang-lto): + +* Splitting integer, string, float and switch comparisons so AFL++ can easier + solve these. This is an important option if you do not have a very good and + large input corpus. This technique is called laf-intel or COMPCOV. To use this + set the following environment variable before compiling the target: `export + AFL_LLVM_LAF_ALL=1` You can read more about this in + [instrumentation/README.laf-intel.md](../instrumentation/README.laf-intel.md). +* A different technique (and usually a better one than laf-intel) is to + instrument the target so that any compare values in the target are sent to + AFL++ which then tries to put these values into the fuzzing data at different + locations. This technique is very fast and good - if the target does not + transform input data before comparison. Therefore this technique is called + `input to state` or `redqueen`. If you want to use this technique, then you + have to compile the target twice, once specifically with/for this mode by + setting `AFL_LLVM_CMPLOG=1`, and pass this binary to afl-fuzz via the `-c` + parameter. Note that you can compile also just a cmplog binary and use that + for both, however, there will be a performance penalty. You can read more + about this in + [instrumentation/README.cmplog.md](../instrumentation/README.cmplog.md). + +If you use LTO, LLVM or GCC_PLUGIN mode +(afl-clang-fast/afl-clang-lto/afl-gcc-fast) you have the option to selectively +only instrument parts of the target that you are interested in: + +* To instrument only those parts of the target that you are interested in create + a file with all the filenames of the source code that should be instrumented. + For afl-clang-lto and afl-gcc-fast - or afl-clang-fast if a mode other than + DEFAULT/PCGUARD is used or you have llvm > 10.0.0 - just put one filename or + function per line (no directory information necessary for filenames9, and + either set `export AFL_LLVM_ALLOWLIST=allowlist.txt` **or** `export + AFL_LLVM_DENYLIST=denylist.txt` - depending on if you want per default to + instrument unless noted (DENYLIST) or not perform instrumentation unless + requested (ALLOWLIST). **NOTE:** During optimization functions might be + inlined and then would not match! See + [instrumentation/README.instrument_list.md](../instrumentation/README.instrument_list.md) + +There are many more options and modes available, however, these are most of the +time less effective. See: +* [instrumentation/README.llvm.md#6) AFL++ Context Sensitive Branch Coverage](../instrumentation/README.llvm.md#6-afl-context-sensitive-branch-coverage) +* [instrumentation/README.llvm.md#7) AFL++ N-Gram Branch Coverage](../instrumentation/README.llvm.md#7-afl-n-gram-branch-coverage) + +AFL++ performs "never zero" counting in its bitmap. You can read more about this +here: +* [instrumentation/README.llvm.md#8-neverzero-counters](../instrumentation/README.llvm.md#8-neverzero-counters) + +### c) Selecting sanitizers + +It is possible to use sanitizers when instrumenting targets for fuzzing, which +allows you to find bugs that would not necessarily result in a crash. + +Note that sanitizers have a huge impact on CPU (= less executions per second) +and RAM usage. Also you should only run one afl-fuzz instance per sanitizer +type. This is enough because a use-after-free bug will be picked up, e.g., by +ASAN (address sanitizer) anyway when syncing to other fuzzing instances, so not +all fuzzing instances need to be instrumented with ASAN. + +The following sanitizers have built-in support in AFL++: +* ASAN = Address SANitizer, finds memory corruption vulnerabilities like + use-after-free, NULL pointer dereference, buffer overruns, etc. Enabled with + `export AFL_USE_ASAN=1` before compiling. +* MSAN = Memory SANitizer, finds read access to uninitialized memory, e.g., a + local variable that is defined and read before it is even set. Enabled with + `export AFL_USE_MSAN=1` before compiling. +* UBSAN = Undefined Behavior SANitizer, finds instances where - by the C and C++ + standards - undefined behavior happens, e.g., adding two signed integers + together where the result is larger than a signed integer can hold. Enabled + with `export AFL_USE_UBSAN=1` before compiling. +* CFISAN = Control Flow Integrity SANitizer, finds instances where the control + flow is found to be illegal. Originally this was rather to prevent return + oriented programming exploit chains from functioning, in fuzzing this is + mostly reduced to detecting type confusion vulnerabilities - which is, + however, one of the most important and dangerous C++ memory corruption + classes! Enabled with `export AFL_USE_CFISAN=1` before compiling. +* TSAN = Thread SANitizer, finds thread race conditions. Enabled with `export + AFL_USE_TSAN=1` before compiling. +* LSAN = Leak SANitizer, finds memory leaks in a program. This is not really a + security issue, but for developers this can be very valuable. Note that unlike + the other sanitizers above this needs `__AFL_LEAK_CHECK();` added to all areas + of the target source code where you find a leak check necessary! Enabled with + `export AFL_USE_LSAN=1` before compiling. + +It is possible to further modify the behavior of the sanitizers at run-time by +setting `ASAN_OPTIONS=...`, `LSAN_OPTIONS` etc. - the available parameters can +be looked up in the sanitizer documentation of llvm/clang. afl-fuzz, however, +requires some specific parameters important for fuzzing to be set. If you want +to set your own, it might bail and report what it is missing. + +Note that some sanitizers cannot be used together, e.g., ASAN and MSAN, and +others often cannot work together because of target weirdness, e.g., ASAN and +CFISAN. You might need to experiment which sanitizers you can combine in a +target (which means more instances can be run without a sanitized target, which +is more effective). + +### d) Modifying the target + +If the target has features that make fuzzing more difficult, e.g., checksums, +HMAC, etc., then modify the source code so that checks for these values are +removed. This can even be done safely for source code used in operational +products by eliminating these checks within these AFL++ specific blocks: + +``` +#ifdef FUZZING_BUILD_MODE_UNSAFE_FOR_PRODUCTION + // say that the checksum or HMAC was fine - or whatever is required + // to eliminate the need for the fuzzer to guess the right checksum + return 0; +#endif +``` + +All AFL++ compilers will set this preprocessor definition automatically. + +### e) Instrumenting the target + +In this step the target source code is compiled so that it can be fuzzed. + +Basically you have to tell the target build system that the selected AFL++ +compiler is used. Also - if possible - you should always configure the build +system such that the target is compiled statically and not dynamically. How to +do this is described below. + +The #1 rule when instrumenting a target is: avoid instrumenting shared libraries +at all cost. You would need to set LD_LIBRARY_PATH to point to these, you could +accidentally type "make install" and install them system wide - so don't. Really +don't. **Always compile libraries you want to have instrumented as static and +link these to the target program!** + +Then build the target. (Usually with `make`) + +**NOTES** + +1. Sometimes configure and build systems are fickle and do not like stderr + output (and think this means a test failure) - which is something AFL++ likes + to do to show statistics. It is recommended to disable AFL++ instrumentation + reporting via `export AFL_QUIET=1`. + +2. Sometimes configure and build systems error on warnings - these should be + disabled (e.g., `--disable-werror` for some configure scripts). + +3. In case the configure/build system complains about AFL++'s compiler and + aborts, then set `export AFL_NOOPT=1` which will then just behave like the + real compiler. This option has to be unset again before building the target! + +#### configure + +For `configure` build systems this is usually done by: + +`CC=afl-clang-fast CXX=afl-clang-fast++ ./configure --disable-shared` + +Note that if you are using the (better) afl-clang-lto compiler you also have to +set AR to llvm-ar[-VERSION] and RANLIB to llvm-ranlib[-VERSION] - as is +described in [instrumentation/README.lto.md](../instrumentation/README.lto.md). + +#### cmake + +For `cmake` build systems this is usually done by: + +`mkdir build; cd build; cmake -DCMAKE_C_COMPILER=afl-cc -DCMAKE_CXX_COMPILER=afl-c++ ..` + +Note that if you are using the (better) afl-clang-lto compiler you also have to +set AR to llvm-ar[-VERSION] and RANLIB to llvm-ranlib[-VERSION] - as is +described in [instrumentation/README.lto.md](../instrumentation/README.lto.md). + +#### meson + +For meson you have to set the AFL++ compiler with the very first command! +`CC=afl-cc CXX=afl-c++ meson` + +#### other build systems or if configure/cmake didn't work + +Sometimes cmake and configure do not pick up the AFL++ compiler, or the +ranlib/ar that is needed - because this was just not foreseen by the developer +of the target. Or they have non-standard options. Figure out if there is a +non-standard way to set this, otherwise set up the build normally and edit the +generated build environment afterwards manually to point it to the right +compiler (and/or ranlib and ar). + +### f) Better instrumentation + +If you just fuzz a target program as-is you are wasting a great opportunity for +much more fuzzing speed. + +This variant requires the usage of afl-clang-lto, afl-clang-fast or +afl-gcc-fast. + +It is the so-called `persistent mode`, which is much, much faster but requires +that you code a source file that is specifically calling the target functions +that you want to fuzz, plus a few specific AFL++ functions around it. See +[instrumentation/README.persistent_mode.md](../instrumentation/README.persistent_mode.md) +for details. + +Basically if you do not fuzz a target in persistent mode, then you are just +doing it for a hobby and not professionally :-). + +### g) libfuzzer fuzzer harnesses with LLVMFuzzerTestOneInput() + +libfuzzer `LLVMFuzzerTestOneInput()` harnesses are the defacto standard for +fuzzing, and they can be used with AFL++ (and honggfuzz) as well! + +Compiling them is as simple as: + +``` +afl-clang-fast++ -fsanitize=fuzzer -o harness harness.cpp targetlib.a +``` + +You can even use advanced libfuzzer features like `FuzzedDataProvider`, +`LLVMFuzzerMutate()` etc. and they will work! + +The generated binary is fuzzed with afl-fuzz like any other fuzz target. + +Bonus: the target is already optimized for fuzzing due to persistent mode and +shared-memory test cases and hence gives you the fastest speed possible. + +For more information, see +[utils/aflpp_driver/README.md](../utils/aflpp_driver/README.md). + +## 2. Preparing the fuzzing campaign + +As you fuzz the target with mutated input, having as diverse inputs for the +target as possible improves the efficiency a lot. + +### a) Collecting inputs + +To operate correctly, the fuzzer requires one or more starting files that +contain a good example of the input data normally expected by the targeted +application. + +Try to gather valid inputs for the target from wherever you can. E.g., if it is +the PNG picture format, try to find as many PNG files as possible, e.g., from +reported bugs, test suites, random downloads from the internet, unit test case +data - from all kind of PNG software. + +If the input format is not known, you can also modify a target program to write +normal data it receives and processes to a file and use these. + +You can find many good examples of starting files in the +[testcases/](../testcases) subdirectory that comes with this tool. + +### b) Making the input corpus unique + +Use the AFL++ tool `afl-cmin` to remove inputs from the corpus that do not +produce a new path in the target. + +Put all files from step a) into one directory, e.g., INPUTS. + +If the target program is to be called by fuzzing as `bin/target -d INPUTFILE` +the run afl-cmin like this: + +`afl-cmin -i INPUTS -o INPUTS_UNIQUE -- bin/target -d @@` + +Note that the INPUTFILE argument that the target program would read from has to +be set as `@@`. + +If the target reads from stdin instead, just omit the `@@` as this is the +default. + +This step is highly recommended! + +### c) Minimizing all corpus files + +The shorter the input files that still traverse the same path within the target, +the better the fuzzing will be. This minimization is done with `afl-tmin`, +however, it is a long process as this has to be done for every file: + +``` +mkdir input +cd INPUTS_UNIQUE +for i in *; do + afl-tmin -i "$i" -o "../input/$i" -- bin/target -d @@ +done +``` + +This step can also be parallelized, e.g., with `parallel`. Note that this step +is rather optional though. + +### Done! + +The INPUTS_UNIQUE/ directory from step b) - or even better the directory input/ +if you minimized the corpus in step c) - is the resulting input corpus directory +to be used in fuzzing! :-) + +## 3. Fuzzing the target + +In this final step, fuzz the target. There are not that many important options +to run the target - unless you want to use many CPU cores/threads for the +fuzzing, which will make the fuzzing much more useful. + +If you just use one CPU for fuzzing, then you are fuzzing just for fun and not +seriously :-) + +### a) Running afl-fuzz + +Before you do even a test run of afl-fuzz execute `sudo afl-system-config` (on +the host if you execute afl-fuzz in a docker container). This reconfigures the +system for optimal speed - which afl-fuzz checks and bails otherwise. Set +`export AFL_SKIP_CPUFREQ=1` for afl-fuzz to skip this check if you cannot run +afl-system-config with root privileges on the host for whatever reason. + +Note there is also `sudo afl-persistent-config` which sets additional permanent +boot options for a much better fuzzing performance. + +Note that both scripts improve your fuzzing performance but also decrease your +system protection against attacks! So set strong firewall rules and only expose +SSH as a network service if you use these (which is highly recommended). + +If you have an input corpus from step 2, then specify this directory with the +`-i` option. Otherwise, create a new directory and create a file with any +content as test data in there. + +If you do not want anything special, the defaults are already usually best, +hence all you need is to specify the seed input directory with the result of +step [2a) Collect inputs](#a-collect-inputs): + +`afl-fuzz -i input -o output -- bin/target -d @@` + +Note that the directory specified with `-o` will be created if it does not +exist. + +It can be valuable to run afl-fuzz in a screen or tmux shell so you can log off, +or afl-fuzz is not aborted if you are running it in a remote ssh session where +the connection fails in between. Only do that though once you have verified that +your fuzzing setup works! Run it like `screen -dmS afl-main -- afl-fuzz -M +main-$HOSTNAME -i ...` and it will start away in a screen session. To enter this +session, type `screen -r afl-main`. You see - it makes sense to name the screen +session same as the afl-fuzz -M/-S naming :-) For more information on screen or +tmux, check their documentation. + +If you need to stop and re-start the fuzzing, use the same command line options +(or even change them by selecting a different power schedule or another mutation +mode!) and switch the input directory with a dash (`-`): + +`afl-fuzz -i - -o output -- bin/target -d @@` + +Adding a dictionary is helpful. See the directory +[dictionaries/](../dictionaries/) if something is already included for your data +format, and tell afl-fuzz to load that dictionary by adding `-x +dictionaries/FORMAT.dict`. With afl-clang-lto, you have an autodictionary +generation for which you need to do nothing except to use afl-clang-lto as the +compiler. You also have the option to generate a dictionary yourself, see +[utils/libtokencap/README.md](../utils/libtokencap/README.md). + +afl-fuzz has a variety of options that help to workaround target quirks like +specific locations for the input file (`-f`), performing deterministic fuzzing +(`-D`) and many more. Check out `afl-fuzz -h`. + +We highly recommend that you set a memory limit for running the target with `-m` +which defines the maximum memory in MB. This prevents a potential out-of-memory +problem for your system plus helps you detect missing `malloc()` failure +handling in the target. Play around with various -m values until you find one +that safely works for all your input seeds (if you have good ones and then +double or quadruple that. + +By default, afl-fuzz never stops fuzzing. To terminate AFL++, press Control-C or +send a signal SIGINT. You can limit the number of executions or approximate +runtime in seconds with options also. + +When you start afl-fuzz you will see a user interface that shows what the status +is: + + + +All labels are explained in +[afl-fuzz_approach.md#understanding-the-status-screen](afl-fuzz_approach.md#understanding-the-status-screen). + +### b) Keeping memory use and timeouts in check + +Memory limits are not enforced by afl-fuzz by default and the system may run out +of memory. You can decrease the memory with the `-m` option, the value is in MB. +If this is too small for the target, you can usually see this by afl-fuzz +bailing with the message that it could not connect to the forkserver. + +Consider setting low values for `-m` and `-t`. + +For programs that are nominally very fast, but get sluggish for some inputs, you +can also try setting `-t` values that are more punishing than what `afl-fuzz` +dares to use on its own. On fast and idle machines, going down to `-t 5` may be +a viable plan. + +The `-m` parameter is worth looking at, too. Some programs can end up spending a +fair amount of time allocating and initializing megabytes of memory when +presented with pathological inputs. Low `-m` values can make them give up sooner +and not waste CPU time. + +### c) Using multiple cores + +If you want to seriously fuzz, then use as many cores/threads as possible to +fuzz your target. + +On the same machine - due to the design of how AFL++ works - there is a maximum +number of CPU cores/threads that are useful, use more and the overall +performance degrades instead. This value depends on the target, and the limit is +between 32 and 64 cores per machine. + +If you have the RAM, it is highly recommended run the instances with a caching +of the test cases. Depending on the average test case size (and those found +during fuzzing) and their number, a value between 50-500MB is recommended. You +can set the cache size (in MB) by setting the environment variable +`AFL_TESTCACHE_SIZE`. + +There should be one main fuzzer (`-M main-$HOSTNAME` option) and as many +secondary fuzzers (e.g., `-S variant1`) as you have cores that you use. Every +-M/-S entry needs a unique name (that can be whatever), however, the same -o +output directory location has to be used for all instances. + +For every secondary fuzzer there should be a variation, e.g.: +* one should fuzz the target that was compiled differently: with sanitizers + activated (`export AFL_USE_ASAN=1 ; export AFL_USE_UBSAN=1 ; export + AFL_USE_CFISAN=1`) +* one or two should fuzz the target with CMPLOG/redqueen (see above), at least + one cmplog instance should follow transformations (`-l AT`) +* one to three fuzzers should fuzz a target compiled with laf-intel/COMPCOV (see + above). Important note: If you run more than one laf-intel/COMPCOV fuzzer and + you want them to share their intermediate results, the main fuzzer (`-M`) must + be one of them! (Although this is not really recommended.) + +All other secondaries should be used like this: +* a quarter to a third with the MOpt mutator enabled: `-L 0` +* run with a different power schedule, recommended are: + `fast (default), explore, coe, lin, quad, exploit and rare` which you can set + with, e.g., `-p explore` +* a few instances should use the old queue cycling with `-Z` + +Also, it is recommended to set `export AFL_IMPORT_FIRST=1` to load test cases +from other fuzzers in the campaign first. + +If you have a large corpus, a corpus from a previous run or are fuzzing in a CI, +then also set `export AFL_CMPLOG_ONLY_NEW=1` and `export AFL_FAST_CAL=1`. + +You can also use different fuzzers. If you are using AFL spinoffs or AFL +conforming fuzzers, then just use the same -o directory and give it a unique +`-S` name. Examples are: +* [Fuzzolic](https://github.com/season-lab/fuzzolic) +* [symcc](https://github.com/eurecom-s3/symcc/) +* [Eclipser](https://github.com/SoftSec-KAIST/Eclipser/) +* [AFLsmart](https://github.com/aflsmart/aflsmart) +* [FairFuzz](https://github.com/carolemieux/afl-rb) +* [Neuzz](https://github.com/Dongdongshe/neuzz) +* [Angora](https://github.com/AngoraFuzzer/Angora) + +A long list can be found at +[https://github.com/Microsvuln/Awesome-AFL](https://github.com/Microsvuln/Awesome-AFL). + +However, you can also sync AFL++ with honggfuzz, libfuzzer with `-entropic=1`, +etc. Just show the main fuzzer (-M) with the `-F` option where the queue/work +directory of a different fuzzer is, e.g., `-F /src/target/honggfuzz`. Using +honggfuzz (with `-n 1` or `-n 2`) and libfuzzer in parallel is highly +recommended! + +### d) Using multiple machines for fuzzing + +Maybe you have more than one machine you want to fuzz the same target on. Start +the `afl-fuzz` (and perhaps libfuzzer, honggfuzz, ...) orchestra as you like, +just ensure that your have one and only one `-M` instance per server, and that +its name is unique, hence the recommendation for `-M main-$HOSTNAME`. + +Now there are three strategies on how you can sync between the servers: +* never: sounds weird, but this makes every server an island and has the chance + the each follow different paths into the target. You can make this even more + interesting by even giving different seeds to each server. +* regularly (~4h): this ensures that all fuzzing campaigns on the servers "see" + the same thing. It is like fuzzing on a huge server. +* in intervals of 1/10th of the overall expected runtime of the fuzzing you + sync. This tries a bit to combine both. have some individuality of the paths + each campaign on a server explores, on the other hand if one gets stuck where + another found progress this is handed over making it unstuck. + +The syncing process itself is very simple. As the `-M main-$HOSTNAME` instance +syncs to all `-S` secondaries as well as to other fuzzers, you have to copy only +this directory to the other machines. + +Lets say all servers have the `-o out` directory in /target/foo/out, and you +created a file `servers.txt` which contains the hostnames of all participating +servers, plus you have an ssh key deployed to all of them, then run: + +```bash +for FROM in `cat servers.txt`; do + for TO in `cat servers.txt`; do + rsync -rlpogtz --rsh=ssh $FROM:/target/foo/out/main-$FROM $TO:target/foo/out/ + done +done +``` + +You can run this manually, per cron job - as you need it. There is a more +complex and configurable script in `utils/distributed_fuzzing`. + +### e) The status of the fuzz campaign + +AFL++ comes with the `afl-whatsup` script to show the status of the fuzzing +campaign. + +Just supply the directory that afl-fuzz is given with the `-o` option and you +will see a detailed status of every fuzzer in that campaign plus a summary. + +To have only the summary, use the `-s` switch, e.g., `afl-whatsup -s out/`. + +If you have multiple servers, then use the command after a sync or you have to +execute this script per server. + +Another tool to inspect the current state and history of a specific instance is +afl-plot, which generates an index.html file and a graphs that show how the +fuzzing instance is performing. The syntax is `afl-plot instance_dir web_dir`, +e.g., `afl-plot out/default /srv/www/htdocs/plot`. + +### f) Stopping fuzzing, restarting fuzzing, adding new seeds + +To stop an afl-fuzz run, press Control-C. + +To restart an afl-fuzz run, just reuse the same command line but replace the `-i +directory` with `-i -` or set `AFL_AUTORESUME=1`. + +If you want to add new seeds to a fuzzing campaign you can run a temporary +fuzzing instance, e.g., when your main fuzzer is using `-o out` and the new +seeds are in `newseeds/` directory: + +``` +AFL_BENCH_JUST_ONE=1 AFL_FAST_CAL=1 afl-fuzz -i newseeds -o out -S newseeds -- ./target +``` + +### g) Checking the coverage of the fuzzing + +The `paths found` value is a bad indicator for checking how good the coverage +is. + +A better indicator - if you use default llvm instrumentation with at least +version 9 - is to use `afl-showmap` with the collect coverage option `-C` on the +output directory: + +``` +$ afl-showmap -C -i out -o /dev/null -- ./target -params @@ +... +[*] Using SHARED MEMORY FUZZING feature. +[*] Target map size: 9960 +[+] Processed 7849 input files. +[+] Captured 4331 tuples (highest value 255, total values 67130596) in '/dev/nul +l'. +[+] A coverage of 4331 edges were achieved out of 9960 existing (43.48%) with 7849 input files. +``` + +It is even better to check out the exact lines of code that have been reached - +and which have not been found so far. + +An "easy" helper script for this is +[https://github.com/vanhauser-thc/afl-cov](https://github.com/vanhauser-thc/afl-cov), +just follow the README of that separate project. + +If you see that an important area or a feature has not been covered so far, then +try to find an input that is able to reach that and start a new secondary in +that fuzzing campaign with that seed as input, let it run for a few minutes, +then terminate it. The main node will pick it up and make it available to the +other secondary nodes over time. Set `export AFL_NO_AFFINITY=1` or `export +AFL_TRY_AFFINITY=1` if you have no free core. + +Note that in nearly all cases you can never reach full coverage. A lot of +functionality is usually dependent on exclusive options that would need +individual fuzzing campaigns each with one of these options set. E.g., if you +fuzz a library to convert image formats and your target is the png to tiff API, +then you will not touch any of the other library APIs and features. + +### h) How long to fuzz a target? + +This is a difficult question. Basically, if no new path is found for a long time +(e.g., for a day or a week), then you can expect that your fuzzing won't be +fruitful anymore. However, often this just means that you should switch out +secondaries for others, e.g., custom mutator modules, sync to very different +fuzzers, etc. + +Keep the queue/ directory (for future fuzzings of the same or similar targets) +and use them to seed other good fuzzers like libfuzzer with the -entropic switch +or honggfuzz. + +### i) Improve the speed! + +* Use [persistent mode](../instrumentation/README.persistent_mode.md) (x2-x20 + speed increase) +* If you do not use shmem persistent mode, use `AFL_TMPDIR` to point the input + file on a tempfs location, see [env_variables.md](env_variables.md) +* Linux: Improve kernel performance: modify `/etc/default/grub`, set + `GRUB_CMDLINE_LINUX_DEFAULT="ibpb=off ibrs=off kpti=off l1tf=off mds=off + mitigations=off no_stf_barrier noibpb noibrs nopcid nopti + nospec_store_bypass_disable nospectre_v1 nospectre_v2 pcid=off pti=off + spec_store_bypass_disable=off spectre_v2=off stf_barrier=off"`; then + `update-grub` and `reboot` (warning: makes the system more insecure) - you can + also just run `sudo afl-persistent-config` +* Linux: Running on an `ext2` filesystem with `noatime` mount option will be a + bit faster than on any other journaling filesystem +* Use your cores! [3c) Using multiple cores](#c-using-multiple-cores) +* Run `sudo afl-system-config` before starting the first afl-fuzz instance after + a reboot + +### j) Going beyond crashes + +Fuzzing is a wonderful and underutilized technique for discovering non-crashing +design and implementation errors, too. Quite a few interesting bugs have been +found by modifying the target programs to call `abort()` when say: + +- Two bignum libraries produce different outputs when given the same + fuzzer-generated input. + +- An image library produces different outputs when asked to decode the same + input image several times in a row. + +- A serialization/deserialization library fails to produce stable outputs when + iteratively serializing and deserializing fuzzer-supplied data. + +- A compression library produces an output inconsistent with the input file when + asked to compress and then decompress a particular blob. + +Implementing these or similar sanity checks usually takes very little time; if +you are the maintainer of a particular package, you can make this code +conditional with `#ifdef FUZZING_BUILD_MODE_UNSAFE_FOR_PRODUCTION` (a flag also +shared with libfuzzer and honggfuzz) or `#ifdef __AFL_COMPILER` (this one is +just for AFL++). + +### k) Known limitations & areas for improvement + +Here are some of the most important caveats for AFL++: + +- AFL++ detects faults by checking for the first spawned process dying due to a + signal (SIGSEGV, SIGABRT, etc.). Programs that install custom handlers for + these signals may need to have the relevant code commented out. In the same + vein, faults in child processes spawned by the fuzzed target may evade + detection unless you manually add some code to catch that. + +- As with any other brute-force tool, the fuzzer offers limited coverage if + encryption, checksums, cryptographic signatures, or compression are used to + wholly wrap the actual data format to be tested. + + To work around this, you can comment out the relevant checks (see + utils/libpng_no_checksum/ for inspiration); if this is not possible, you can + also write a postprocessor, one of the hooks of custom mutators. See + [custom_mutators.md](custom_mutators.md) on how to use + `AFL_CUSTOM_MUTATOR_LIBRARY`. + +- There are some unfortunate trade-offs with ASAN and 64-bit binaries. This + isn't due to any specific fault of afl-fuzz. + +- There is no direct support for fuzzing network services, background daemons, + or interactive apps that require UI interaction to work. You may need to make + simple code changes to make them behave in a more traditional way. Preeny may + offer a relatively simple option, too - see: + [https://github.com/zardus/preeny](https://github.com/zardus/preeny) + + Some useful tips for modifying network-based services can be also found at: + [https://www.fastly.com/blog/how-to-fuzz-server-american-fuzzy-lop](https://www.fastly.com/blog/how-to-fuzz-server-american-fuzzy-lop) + +- Occasionally, sentient machines rise against their creators. If this happens + to you, please consult + [https://lcamtuf.coredump.cx/prep/](https://lcamtuf.coredump.cx/prep/). + +Beyond this, see [INSTALL.md](INSTALL.md) for platform-specific tips. + +## 4. Triaging crashes + +The coverage-based grouping of crashes usually produces a small data set that +can be quickly triaged manually or with a very simple GDB or Valgrind script. +Every crash is also traceable to its parent non-crashing test case in the queue, +making it easier to diagnose faults. + +Having said that, it's important to acknowledge that some fuzzing crashes can be +difficult to quickly evaluate for exploitability without a lot of debugging and +code analysis work. To assist with this task, afl-fuzz supports a very unique +"crash exploration" mode enabled with the -C flag. + +In this mode, the fuzzer takes one or more crashing test cases as the input and +uses its feedback-driven fuzzing strategies to very quickly enumerate all code +paths that can be reached in the program while keeping it in the crashing state. + +Mutations that do not result in a crash are rejected; so are any changes that do +not affect the execution path. + +The output is a small corpus of files that can be very rapidly examined to see +what degree of control the attacker has over the faulting address, or whether it +is possible to get past an initial out-of-bounds read - and see what lies +beneath. + +Oh, one more thing: for test case minimization, give afl-tmin a try. The tool +can be operated in a very simple way: + +```shell +./afl-tmin -i test_case -o minimized_result -- /path/to/program [...] +``` + +The tool works with crashing and non-crashing test cases alike. In the crash +mode, it will happily accept instrumented and non-instrumented binaries. In the +non-crashing mode, the minimizer relies on standard AFL++ instrumentation to +make the file simpler without altering the execution path. + +The minimizer accepts the -m, -t, -f and @@ syntax in a manner compatible with +afl-fuzz. + +Another tool in AFL++ is the afl-analyze tool. It takes an input file, attempts +to sequentially flip bytes, and observes the behavior of the tested program. It +then color-codes the input based on which sections appear to be critical, and +which are not; while not bulletproof, it can often offer quick insights into +complex file formats. + +## 5. CI fuzzing + +Some notes on CI fuzzing - this fuzzing is different to normal fuzzing campaigns +as these are much shorter runnings. + +1. Always: + * LTO has a much longer compile time which is diametrical to short fuzzing - + hence use afl-clang-fast instead. + * If you compile with CMPLOG, then you can save fuzzing time and reuse that + compiled target for both the `-c` option and the main fuzz target. This + will impact the speed by ~15% though. + * `AFL_FAST_CAL` - Enable fast calibration, this halves the time the + saturated corpus needs to be loaded. + * `AFL_CMPLOG_ONLY_NEW` - only perform cmplog on new found paths, not the + initial corpus as this very likely has been done for them already. + * Keep the generated corpus, use afl-cmin and reuse it every time! + +2. Additionally randomize the AFL++ compilation options, e.g.: + * 40% for `AFL_LLVM_CMPLOG` + * 10% for `AFL_LLVM_LAF_ALL` + +3. Also randomize the afl-fuzz runtime options, e.g.: + * 65% for `AFL_DISABLE_TRIM` + * 50% use a dictionary generated by `AFL_LLVM_DICT2FILE` + * 40% use MOpt (`-L 0`) + * 40% for `AFL_EXPAND_HAVOC_NOW` + * 20% for old queue processing (`-Z`) + * for CMPLOG targets, 60% for `-l 2`, 40% for `-l 3` + +4. Do *not* run any `-M` modes, just running `-S` modes is better for CI + fuzzing. `-M` enables old queue handling etc. which is good for a fuzzing + campaign but not good for short CI runs. + +How this can look like can, e.g., be seen at AFL++'s setup in Google's +[oss-fuzz](https://github.com/google/oss-fuzz/blob/master/infra/base-images/base-builder/compile_afl) +and +[clusterfuzz](https://github.com/google/clusterfuzz/blob/master/src/clusterfuzz/_internal/bot/fuzzers/afl/launcher.py). + +## The End + +Check out the [FAQ](FAQ.md) if it maybe answers your question (that you might +not even have known you had ;-) ). + +This is basically all you need to know to professionally run fuzzing campaigns. +If you want to know more, the tons of texts in [docs/](./) will have you +covered. + +Note that there are also a lot of tools out there that help fuzzing with AFL++ +(some might be deprecated or unsupported), see +[third_party_tools.md](third_party_tools.md). \ No newline at end of file diff --git a/docs/ideas.md b/docs/ideas.md index 325e7031..52b07c26 100644 --- a/docs/ideas.md +++ b/docs/ideas.md @@ -1,58 +1,57 @@ # Ideas for AFL++ -In the following, we describe a variety of ideas that could be implemented -for future AFL++ versions. +In the following, we describe a variety of ideas that could be implemented for +future AFL++ versions. ## Analysis software -Currently analysis is done by using afl-plot, which is rather outdated. -A GTK or browser tool to create run-time analysis based on fuzzer_stats, -queue/id* information and plot_data that allows for zooming in and out, -changing min/max display values etc. and doing that for a single run, -different runs and campaigns vs campaigns. -Interesting values are execs, and execs/s, edges discovered (total, when -each edge was discovered and which other fuzzer share finding that edge), -test cases executed. -It should be clickable which value is X and Y axis, zoom factor, log scaling -on-off, etc. +Currently analysis is done by using afl-plot, which is rather outdated. A GTK or +browser tool to create run-time analysis based on fuzzer_stats, queue/id* +information and plot_data that allows for zooming in and out, changing min/max +display values etc. and doing that for a single run, different runs and +campaigns vs. campaigns. Interesting values are execs, and execs/s, edges +discovered (total, when each edge was discovered and which other fuzzer share +finding that edge), test cases executed. It should be clickable which value is X +and Y axis, zoom factor, log scaling on-off, etc. Mentor: vanhauser-thc ## WASM Instrumentation Currently, AFL++ can be used for source code fuzzing and traditional binaries. -With the rise of WASM as compile target, however, a novel way of -instrumentation needs to be implemented for binaries compiled to Webassembly. -This can either be done by inserting instrumentation directly into the -WASM AST, or by patching feedback into a WASM VMs of choice, similar to -the current Unicorn instrumentation. +With the rise of WASM as compile target, however, a novel way of instrumentation +needs to be implemented for binaries compiled to Webassembly. This can either be +done by inserting instrumentation directly into the WASM AST, or by patching +feedback into a WASM VMs of choice, similar to the current Unicorn +instrumentation. Mentor: any ## Support other programming languages Other programming languages also use llvm hence they could (easily?) supported -for fuzzing, e.g. mono, swift, go, kotlin native, fortran, ... +for fuzzing, e.g., mono, swift, go, kotlin native, fortran, ... -GCC also supports: Objective-C, Fortran, Ada, Go, and D -(according to [Gcc homepage](https://gcc.gnu.org/)) +GCC also supports: Objective-C, Fortran, Ada, Go, and D (according to +[Gcc homepage](https://gcc.gnu.org/)) -LLVM is also used by: Rust, LLGo (Go), kaleidoscope (Haskell), flang (Fortran), emscripten (JavaScript, WASM), ilwasm (CIL (C#)) -(according to [LLVM frontends](https://gist.github.com/axic/62d66fb9d8bccca6cc48fa9841db9241)) +LLVM is also used by: Rust, LLGo (Go), kaleidoscope (Haskell), flang (Fortran), +emscripten (JavaScript, WASM), ilwasm (CIL (C#)) (according to +[LLVM frontends](https://gist.github.com/axic/62d66fb9d8bccca6cc48fa9841db9241)) Mentor: vanhauser-thc ## Machine Learning -Something with machine learning, better than [NEUZZ](https://github.com/dongdongshe/neuzz) :-) -Either improve a single mutator thorugh learning of many different bugs -(a bug class) or gather deep insights about a single target beforehand -(CFG, DFG, VFG, ...?) and improve performance for a single target. +Something with machine learning, better than +[NEUZZ](https://github.com/dongdongshe/neuzz) :-) Either improve a single +mutator through learning of many different bugs (a bug class) or gather deep +insights about a single target beforehand (CFG, DFG, VFG, ...?) and improve +performance for a single target. Mentor: domenukk ## Your idea! -Finally, we are open to proposals! -Create an issue at https://github.com/AFLplusplus/AFLplusplus/issues and let's discuss :-) - +Finally, we are open to proposals! Create an issue at +https://github.com/AFLplusplus/AFLplusplus/issues and let's discuss :-) \ No newline at end of file diff --git a/docs/important_changes.md b/docs/important_changes.md new file mode 100644 index 00000000..d5e67f75 --- /dev/null +++ b/docs/important_changes.md @@ -0,0 +1,58 @@ +# Important changes in AFL++ + +This document lists important changes in AFL++, for example, major behavior +changes. + +## From version 3.00 onwards + +With AFL++ 3.13-3.20, we introduce FRIDA mode (`-O`) to have an alternative for +binary-only fuzzing. It is slower than QEMU mode but works on MacOS, Android, +iOS etc. + +With AFL++ 3.15, we introduced the following changes from previous behaviors: + * Also -M main mode does not do deterministic fuzzing by default anymore + * afl-cmin and afl-showmap -Ci now descent into subdirectories like afl-fuzz + -i does (but note that afl-cmin.bash does not) + +With AFL++ 3.14, we introduced the following changes from previous behaviors: + * afl-fuzz: deterministic fuzzing it not a default for -M main anymore + * afl-cmin/afl-showmap -i now descends into subdirectories (afl-cmin.bash, + however, does not) + +With AFL++ 3.10, we introduced the following changes from previous behaviors: + * The '+' feature of the '-t' option now means to auto-calculate the timeout + with the value given being the maximum timeout. The original meaning of + "skipping timeouts instead of abort" is now inherent to the -t option. + +With AFL++ 3.00, we introduced changes that break some previous AFL and AFL++ +behaviors and defaults: + * There are no llvm_mode and gcc_plugin subdirectories anymore and there is + only one compiler: afl-cc. All previous compilers now symlink to this one. + All instrumentation source code is now in the `instrumentation/` folder. + * The gcc_plugin was replaced with a new version submitted by AdaCore that + supports more features. Thank you! + * QEMU mode got upgraded to QEMU 5.1, but to be able to build this a current + ninja build tool version and python3 setuptools are required. QEMU mode also + got new options like snapshotting, instrumenting specific shared libraries, + etc. Additionally QEMU 5.1 supports more CPU targets so this is really worth + it. + * When instrumenting targets, afl-cc will not supersede optimizations anymore + if any were given. This allows to fuzz targets build regularly like those + for debug or release versions. + * afl-fuzz: + * if neither -M or -S is specified, `-S default` is assumed, so more fuzzers + can easily be added later + * `-i` input directory option now descends into subdirectories. It also does + not fatal on crashes and too large files, instead it skips them and uses + them for splicing mutations + * -m none is now default, set memory limits (in MB) with, e.g., -m 250 + * deterministic fuzzing is now disabled by default (unless using -M) and can + be enabled with -D + * a caching of test cases can now be performed and can be modified by + editing config.h for TESTCASE_CACHE or by specifying the environment + variable `AFL_TESTCACHE_SIZE` (in MB). Good values are between 50-500 + (default: 50). + * -M mains do not perform trimming + * examples/ got renamed to utils/ + * libtokencap/ libdislocator/ and qdbi_mode/ were moved to utils/ + * afl-cmin/afl-cmin.bash now search first in PATH and last in AFL_PATH \ No newline at end of file diff --git a/docs/life_pro_tips.md b/docs/life_pro_tips.md deleted file mode 100644 index 13ffcea0..00000000 --- a/docs/life_pro_tips.md +++ /dev/null @@ -1,87 +0,0 @@ -# AFL "Life Pro Tips" - -Bite-sized advice for those who understand the basics, but can't be bothered -to read or memorize every other piece of documentation for AFL. - -## Get more bang for your buck by using fuzzing dictionaries. - -See [dictionaries/README.md](../dictionaries/README.md) to learn how. - -## You can get the most out of your hardware by parallelizing AFL jobs. - -See [parallel_fuzzing.md](parallel_fuzzing.md) for step-by-step tips. - -## Improve the odds of spotting memory corruption bugs with libdislocator.so! - -It's easy. Consult [utils/libdislocator/README.md](../utils/libdislocator/README.md) for usage tips. - -## Want to understand how your target parses a particular input file? - -Try the bundled `afl-analyze` tool; it's got colors and all! - -## You can visually monitor the progress of your fuzzing jobs. - -Run the bundled `afl-plot` utility to generate browser-friendly graphs. - -## Need to monitor AFL jobs programmatically? -Check out the `fuzzer_stats` file in the AFL output dir or try `afl-whatsup`. - -## Puzzled by something showing up in red or purple in the AFL UI? -It could be important - consult docs/status_screen.md right away! - -## Know your target? Convert it to persistent mode for a huge performance gain! -Consult section #5 in README.llvm.md for tips. - -## Using clang? -Check out instrumentation/ for a faster alternative to afl-gcc! - -## Did you know that AFL can fuzz closed-source or cross-platform binaries? -Check out qemu_mode/README.md and unicorn_mode/README.md for more. - -## Did you know that afl-fuzz can minimize any test case for you? -Try the bundled `afl-tmin` tool - and get small repro files fast! - -## Not sure if a crash is exploitable? AFL can help you figure it out. Specify -`-C` to enable the peruvian were-rabbit mode. - -## Trouble dealing with a machine uprising? Relax, we've all been there. - -Find essential survival tips at http://lcamtuf.coredump.cx/prep/. - -## Want to automatically spot non-crashing memory handling bugs? - -Try running an AFL-generated corpus through ASAN, MSAN, or Valgrind. - -## Good selection of input files is critical to a successful fuzzing job. - -See docs/perf_tips.md for pro tips. - -## You can improve the odds of automatically spotting stack corruption issues. - -Specify `AFL_HARDEN=1` in the environment to enable hardening flags. - -## Bumping into problems with non-reproducible crashes? -It happens, but usually -isn't hard to diagnose. See section #7 in README.md for tips. - -## Fuzzing is not just about memory corruption issues in the codebase. -Add some -sanity-checking `assert()` / `abort()` statements to effortlessly catch logic bugs. - -## Hey kid... pssst... want to figure out how AFL really works? - -Check out docs/technical_details.md for all the gory details in one place! - -## There's a ton of third-party helper tools designed to work with AFL! - -Be sure to check out docs/sister_projects.md before writing your own. - -## Need to fuzz the command-line arguments of a particular program? - -You can find a simple solution in utils/argv_fuzzing. - -## Attacking a format that uses checksums? - -Remove the checksum-checking code or use a postprocessor! -See `afl_custom_post_process` in custom_mutators/examples/example.c for more. - diff --git a/docs/parallel_fuzzing.md b/docs/parallel_fuzzing.md deleted file mode 100644 index 90e12e89..00000000 --- a/docs/parallel_fuzzing.md +++ /dev/null @@ -1,259 +0,0 @@ -# Tips for parallel fuzzing - -This document talks about synchronizing afl-fuzz jobs on a single machine -or across a fleet of systems. See README.md for the general instruction manual. - -Note that this document is rather outdated. please refer to the main document -section on multiple core usage [../README.md#Using multiple cores](../README.md#b-using-multiple-coresthreads) -for up to date strategies! - -## 1) Introduction - -Every copy of afl-fuzz will take up one CPU core. This means that on an -n-core system, you can almost always run around n concurrent fuzzing jobs with -virtually no performance hit (you can use the afl-gotcpu tool to make sure). - -In fact, if you rely on just a single job on a multi-core system, you will -be underutilizing the hardware. So, parallelization is always the right way to -go. - -When targeting multiple unrelated binaries or using the tool in -"non-instrumented" (-n) mode, it is perfectly fine to just start up several -fully separate instances of afl-fuzz. The picture gets more complicated when -you want to have multiple fuzzers hammering a common target: if a hard-to-hit -but interesting test case is synthesized by one fuzzer, the remaining instances -will not be able to use that input to guide their work. - -To help with this problem, afl-fuzz offers a simple way to synchronize test -cases on the fly. - -Note that AFL++ has AFLfast's power schedules implemented. -It is therefore a good idea to use different power schedules if you run -several instances in parallel. See [power_schedules.md](power_schedules.md) - -Alternatively running other AFL spinoffs in parallel can be of value, -e.g. Angora (https://github.com/AngoraFuzzer/Angora/) - -## 2) Single-system parallelization - -If you wish to parallelize a single job across multiple cores on a local -system, simply create a new, empty output directory ("sync dir") that will be -shared by all the instances of afl-fuzz; and then come up with a naming scheme -for every instance - say, "fuzzer01", "fuzzer02", etc. - -Run the first one ("main node", -M) like this: - -``` -./afl-fuzz -i testcase_dir -o sync_dir -M fuzzer01 [...other stuff...] -``` - -...and then, start up secondary (-S) instances like this: - -``` -./afl-fuzz -i testcase_dir -o sync_dir -S fuzzer02 [...other stuff...] -./afl-fuzz -i testcase_dir -o sync_dir -S fuzzer03 [...other stuff...] -``` - -Each fuzzer will keep its state in a separate subdirectory, like so: - - /path/to/sync_dir/fuzzer01/ - -Each instance will also periodically rescan the top-level sync directory -for any test cases found by other fuzzers - and will incorporate them into -its own fuzzing when they are deemed interesting enough. -For performance reasons only -M main node syncs the queue with everyone, the --S secondary nodes will only sync from the main node. - -The difference between the -M and -S modes is that the main instance will -still perform deterministic checks; while the secondary instances will -proceed straight to random tweaks. - -Note that you must always have one -M main instance! -Running multiple -M instances is wasteful! - -You can also monitor the progress of your jobs from the command line with the -provided afl-whatsup tool. When the instances are no longer finding new paths, -it's probably time to stop. - -WARNING: Exercise caution when explicitly specifying the -f option. Each fuzzer -must use a separate temporary file; otherwise, things will go south. One safe -example may be: - -``` -./afl-fuzz [...] -S fuzzer10 -f file10.txt ./fuzzed/binary @@ -./afl-fuzz [...] -S fuzzer11 -f file11.txt ./fuzzed/binary @@ -./afl-fuzz [...] -S fuzzer12 -f file12.txt ./fuzzed/binary @@ -``` - -This is not a concern if you use @@ without -f and let afl-fuzz come up with the -file name. - -## 3) Multiple -M mains - - -There is support for parallelizing the deterministic checks. -This is only needed where - - 1. many new paths are found fast over a long time and it looks unlikely that - main node will ever catch up, and - 2. deterministic fuzzing is actively helping path discovery (you can see this - in the main node for the first for lines in the "fuzzing strategy yields" - section. If the ration `found/attemps` is high, then it is effective. It - most commonly isn't.) - -Only if both are true it is beneficial to have more than one main. -You can leverage this by creating -M instances like so: - -``` -./afl-fuzz -i testcase_dir -o sync_dir -M mainA:1/3 [...] -./afl-fuzz -i testcase_dir -o sync_dir -M mainB:2/3 [...] -./afl-fuzz -i testcase_dir -o sync_dir -M mainC:3/3 [...] -``` - -... where the first value after ':' is the sequential ID of a particular main -instance (starting at 1), and the second value is the total number of fuzzers to -distribute the deterministic fuzzing across. Note that if you boot up fewer -fuzzers than indicated by the second number passed to -M, you may end up with -poor coverage. - -## 4) Syncing with non-AFL fuzzers or independant instances - -A -M main node can be told with the `-F other_fuzzer_queue_directory` option -to sync results from other fuzzers, e.g. libfuzzer or honggfuzz. - -Only the specified directory will by synced into afl, not subdirectories. -The specified directory does not need to exist yet at the start of afl. - -The `-F` option can be passed to the main node several times. - -## 5) Multi-system parallelization - -The basic operating principle for multi-system parallelization is similar to -the mechanism explained in section 2. The key difference is that you need to -write a simple script that performs two actions: - - - Uses SSH with authorized_keys to connect to every machine and retrieve - a tar archive of the /path/to/sync_dir/<main_node(s)> directory local to - the machine. - It is best to use a naming scheme that includes host name and it's being - a main node (e.g. main1, main2) in the fuzzer ID, so that you can do - something like: - - ```sh - for host in `cat HOSTLIST`; do - ssh user@$host "tar -czf - sync/$host_main*/" > $host.tgz - done - ``` - - - Distributes and unpacks these files on all the remaining machines, e.g.: - - ```sh - for srchost in `cat HOSTLIST`; do - for dsthost in `cat HOSTLIST`; do - test "$srchost" = "$dsthost" && continue - ssh user@$srchost 'tar -kxzf -' < $dsthost.tgz - done - done - ``` - -There is an example of such a script in utils/distributed_fuzzing/. - -There are other (older) more featured, experimental tools: - * https://github.com/richo/roving - * https://github.com/MartijnB/disfuzz-afl - -However these do not support syncing just main nodes (yet). - -When developing custom test case sync code, there are several optimizations -to keep in mind: - - - The synchronization does not have to happen very often; running the - task every 60 minutes or even less often at later fuzzing stages is - fine - - - There is no need to synchronize crashes/ or hangs/; you only need to - copy over queue/* (and ideally, also fuzzer_stats). - - - It is not necessary (and not advisable!) to overwrite existing files; - the -k option in tar is a good way to avoid that. - - - There is no need to fetch directories for fuzzers that are not running - locally on a particular machine, and were simply copied over onto that - system during earlier runs. - - - For large fleets, you will want to consolidate tarballs for each host, - as this will let you use n SSH connections for sync, rather than n*(n-1). - - You may also want to implement staged synchronization. For example, you - could have 10 groups of systems, with group 1 pushing test cases only - to group 2; group 2 pushing them only to group 3; and so on, with group - eventually 10 feeding back to group 1. - - This arrangement would allow test interesting cases to propagate across - the fleet without having to copy every fuzzer queue to every single host. - - - You do not want a "main" instance of afl-fuzz on every system; you should - run them all with -S, and just designate a single process somewhere within - the fleet to run with -M. - - - Syncing is only necessary for the main nodes on a system. It is possible - to run main-less with only secondaries. However then you need to find out - which secondary took over the temporary role to be the main node. Look for - the `is_main_node` file in the fuzzer directories, eg. `sync-dir/hostname-*/is_main_node` - -It is *not* advisable to skip the synchronization script and run the fuzzers -directly on a network filesystem; unexpected latency and unkillable processes -in I/O wait state can mess things up. - -## 6) Remote monitoring and data collection - -You can use screen, nohup, tmux, or something equivalent to run remote -instances of afl-fuzz. If you redirect the program's output to a file, it will -automatically switch from a fancy UI to more limited status reports. There is -also basic machine-readable information which is always written to the -fuzzer_stats file in the output directory. Locally, that information can be -interpreted with afl-whatsup. - -In principle, you can use the status screen of the main (-M) instance to -monitor the overall fuzzing progress and decide when to stop. In this -mode, the most important signal is just that no new paths are being found -for a longer while. If you do not have a main instance, just pick any -single secondary instance to watch and go by that. - -You can also rely on that instance's output directory to collect the -synthesized corpus that covers all the noteworthy paths discovered anywhere -within the fleet. Secondary (-S) instances do not require any special -monitoring, other than just making sure that they are up. - -Keep in mind that crashing inputs are *not* automatically propagated to the -main instance, so you may still want to monitor for crashes fleet-wide -from within your synchronization or health checking scripts (see afl-whatsup). - -## 7) Asymmetric setups - -It is perhaps worth noting that all of the following is permitted: - - - Running afl-fuzz with conjunction with other guided tools that can extend - coverage (e.g., via concolic execution). Third-party tools simply need to - follow the protocol described above for pulling new test cases from - out_dir/<fuzzer_id>/queue/* and writing their own finds to sequentially - numbered id:nnnnnn files in out_dir/<ext_tool_id>/queue/*. - - - Running some of the synchronized fuzzers with different (but related) - target binaries. For example, simultaneously stress-testing several - different JPEG parsers (say, IJG jpeg and libjpeg-turbo) while sharing - the discovered test cases can have synergistic effects and improve the - overall coverage. - - (In this case, running one -M instance per target is necessary.) - - - Having some of the fuzzers invoke the binary in different ways. - For example, 'djpeg' supports several DCT modes, configurable with - a command-line flag, while 'dwebp' supports incremental and one-shot - decoding. In some scenarios, going after multiple distinct modes and then - pooling test cases will improve coverage. - - - Much less convincingly, running the synchronized fuzzers with different - starting test cases (e.g., progressive and standard JPEG) or dictionaries. - The synchronization mechanism ensures that the test sets will get fairly - homogeneous over time, but it introduces some initial variability. diff --git a/docs/perf_tips.md b/docs/perf_tips.md deleted file mode 100644 index 1e8fd4d0..00000000 --- a/docs/perf_tips.md +++ /dev/null @@ -1,209 +0,0 @@ -## Tips for performance optimization - - This file provides tips for troubleshooting slow or wasteful fuzzing jobs. - See README.md for the general instruction manual. - -## 1. Keep your test cases small - -This is probably the single most important step to take! Large test cases do -not merely take more time and memory to be parsed by the tested binary, but -also make the fuzzing process dramatically less efficient in several other -ways. - -To illustrate, let's say that you're randomly flipping bits in a file, one bit -at a time. Let's assume that if you flip bit #47, you will hit a security bug; -flipping any other bit just results in an invalid document. - -Now, if your starting test case is 100 bytes long, you will have a 71% chance of -triggering the bug within the first 1,000 execs - not bad! But if the test case -is 1 kB long, the probability that we will randomly hit the right pattern in -the same timeframe goes down to 11%. And if it has 10 kB of non-essential -cruft, the odds plunge to 1%. - -On top of that, with larger inputs, the binary may be now running 5-10x times -slower than before - so the overall drop in fuzzing efficiency may be easily -as high as 500x or so. - -In practice, this means that you shouldn't fuzz image parsers with your -vacation photos. Generate a tiny 16x16 picture instead, and run it through -`jpegtran` or `pngcrunch` for good measure. The same goes for most other types -of documents. - -There's plenty of small starting test cases in ../testcases/ - try them out -or submit new ones! - -If you want to start with a larger, third-party corpus, run `afl-cmin` with an -aggressive timeout on that data set first. - -## 2. Use a simpler target - -Consider using a simpler target binary in your fuzzing work. For example, for -image formats, bundled utilities such as `djpeg`, `readpng`, or `gifhisto` are -considerably (10-20x) faster than the convert tool from ImageMagick - all while exercising roughly the same library-level image parsing code. - -Even if you don't have a lightweight harness for a particular target, remember -that you can always use another, related library to generate a corpus that will -be then manually fed to a more resource-hungry program later on. - -Also note that reading the fuzzing input via stdin is faster than reading from -a file. - -## 3. Use LLVM persistent instrumentation - -The LLVM mode offers a "persistent", in-process fuzzing mode that can -work well for certain types of self-contained libraries, and for fast targets, -can offer performance gains up to 5-10x; and a "deferred fork server" mode -that can offer huge benefits for programs with high startup overhead. Both -modes require you to edit the source code of the fuzzed program, but the -changes often amount to just strategically placing a single line or two. - -If there are important data comparisons performed (e.g. `strcmp(ptr, MAGIC_HDR)`) -then using laf-intel (see instrumentation/README.laf-intel.md) will help `afl-fuzz` a lot -to get to the important parts in the code. - -If you are only interested in specific parts of the code being fuzzed, you can -instrument_files the files that are actually relevant. This improves the speed and -accuracy of afl. See instrumentation/README.instrument_list.md - -## 4. Profile and optimize the binary - -Check for any parameters or settings that obviously improve performance. For -example, the djpeg utility that comes with IJG jpeg and libjpeg-turbo can be -called with: - -```bash - -dct fast -nosmooth -onepass -dither none -scale 1/4 -``` - -...and that will speed things up. There is a corresponding drop in the quality -of decoded images, but it's probably not something you care about. - -In some programs, it is possible to disable output altogether, or at least use -an output format that is computationally inexpensive. For example, with image -transcoding tools, converting to a BMP file will be a lot faster than to PNG. - -With some laid-back parsers, enabling "strict" mode (i.e., bailing out after -first error) may result in smaller files and improved run time without -sacrificing coverage; for example, for sqlite, you may want to specify -bail. - -If the program is still too slow, you can use `strace -tt` or an equivalent -profiling tool to see if the targeted binary is doing anything silly. -Sometimes, you can speed things up simply by specifying `/dev/null` as the -config file, or disabling some compile-time features that aren't really needed -for the job (try `./configure --help`). One of the notoriously resource-consuming -things would be calling other utilities via `exec*()`, `popen()`, `system()`, or -equivalent calls; for example, tar can invoke external decompression tools -when it decides that the input file is a compressed archive. - -Some programs may also intentionally call `sleep()`, `usleep()`, or `nanosleep()`; -vim is a good example of that. Other programs may attempt `fsync()` and so on. -There are third-party libraries that make it easy to get rid of such code, -e.g.: - - https://launchpad.net/libeatmydata - -In programs that are slow due to unavoidable initialization overhead, you may -want to try the LLVM deferred forkserver mode (see README.llvm.md), -which can give you speed gains up to 10x, as mentioned above. - -Last but not least, if you are using ASAN and the performance is unacceptable, -consider turning it off for now, and manually examining the generated corpus -with an ASAN-enabled binary later on. - -## 5. Instrument just what you need - -Instrument just the libraries you actually want to stress-test right now, one -at a time. Let the program use system-wide, non-instrumented libraries for -any functionality you don't actually want to fuzz. For example, in most -cases, it doesn't make to instrument `libgmp` just because you're testing a -crypto app that relies on it for bignum math. - -Beware of programs that come with oddball third-party libraries bundled with -their source code (Spidermonkey is a good example of this). Check `./configure` -options to use non-instrumented system-wide copies instead. - -## 6. Parallelize your fuzzers - -The fuzzer is designed to need ~1 core per job. This means that on a, say, -4-core system, you can easily run four parallel fuzzing jobs with relatively -little performance hit. For tips on how to do that, see parallel_fuzzing.md. - -The `afl-gotcpu` utility can help you understand if you still have idle CPU -capacity on your system. (It won't tell you about memory bandwidth, cache -misses, or similar factors, but they are less likely to be a concern.) - -## 7. Keep memory use and timeouts in check - -Consider setting low values for `-m` and `-t`. - -For programs that are nominally very fast, but get sluggish for some inputs, -you can also try setting `-t` values that are more punishing than what `afl-fuzz` -dares to use on its own. On fast and idle machines, going down to `-t 5` may be -a viable plan. - -The `-m` parameter is worth looking at, too. Some programs can end up spending -a fair amount of time allocating and initializing megabytes of memory when -presented with pathological inputs. Low `-m` values can make them give up sooner -and not waste CPU time. - -## 8. Check OS configuration - -There are several OS-level factors that may affect fuzzing speed: - - - If you have no risk of power loss then run your fuzzing on a tmpfs - partition. This increases the performance noticably. - Alternatively you can use `AFL_TMPDIR` to point to a tmpfs location to - just write the input file to a tmpfs. - - High system load. Use idle machines where possible. Kill any non-essential - CPU hogs (idle browser windows, media players, complex screensavers, etc). - - Network filesystems, either used for fuzzer input / output, or accessed by - the fuzzed binary to read configuration files (pay special attention to the - home directory - many programs search it for dot-files). - - Disable all the spectre, meltdown etc. security countermeasures in the - kernel if your machine is properly separated: - -``` -ibpb=off ibrs=off kpti=off l1tf=off mds=off mitigations=off -no_stf_barrier noibpb noibrs nopcid nopti nospec_store_bypass_disable -nospectre_v1 nospectre_v2 pcid=off pti=off spec_store_bypass_disable=off -spectre_v2=off stf_barrier=off -``` - In most Linux distributions you can put this into a `/etc/default/grub` - variable. - You can use `sudo afl-persistent-config` to set these options for you. - -The following list of changes are made when executing `afl-system-config`: - - - On-demand CPU scaling. The Linux `ondemand` governor performs its analysis - on a particular schedule and is known to underestimate the needs of - short-lived processes spawned by `afl-fuzz` (or any other fuzzer). On Linux, - this can be fixed with: - -``` bash - cd /sys/devices/system/cpu - echo performance | tee cpu*/cpufreq/scaling_governor -``` - - On other systems, the impact of CPU scaling will be different; when fuzzing, - use OS-specific tools to find out if all cores are running at full speed. - - Transparent huge pages. Some allocators, such as `jemalloc`, can incur a - heavy fuzzing penalty when transparent huge pages (THP) are enabled in the - kernel. You can disable this via: - -```bash - echo never > /sys/kernel/mm/transparent_hugepage/enabled -``` - - - Suboptimal scheduling strategies. The significance of this will vary from - one target to another, but on Linux, you may want to make sure that the - following options are set: - -```bash - echo 1 >/proc/sys/kernel/sched_child_runs_first - echo 1 >/proc/sys/kernel/sched_autogroup_enabled -``` - - Setting a different scheduling policy for the fuzzer process - say - `SCHED_RR` - can usually speed things up, too, but needs to be done with - care. - diff --git a/docs/rpc_statsd.md b/docs/rpc_statsd.md index 898ad099..003b9c79 100644 --- a/docs/rpc_statsd.md +++ b/docs/rpc_statsd.md @@ -1,143 +1,190 @@ -# Remote monitoring with StatsD +# Remote monitoring and metrics visualization -StatsD allows you to receive and aggregate metrics from a wide range of applications and retransmit them to the backend of your choice. -This enables you to create nice and readable dashboards containing all the information you need on your fuzzer instances. -No need to write your own statistics parsing system, deploy and maintain it to all your instances, sync with your graph rendering system... +AFL++ can send out metrics as StatsD messages. For remote monitoring and +visualization of the metrics, you can set up a tool chain. For example, with +Prometheus and Grafana. All tools are free and open source. -The available metrics are : +This enables you to create nice and readable dashboards containing all the +information you need on your fuzzer instances. There is no need to write your +own statistics parsing system, deploy and maintain it to all your instances, and +sync with your graph rendering system. + +Compared to the default integrated UI of AFL++, this can help you to visualize +trends and the fuzzing state over time. You might be able to see when the +fuzzing process has reached a state of no progress and visualize what are the +"best strategies" for your targets (according to your own criteria). You can do +so without logging into each instance individually. + + + +This is an example visualization with Grafana. The dashboard can be imported +with [this JSON template](resources/grafana-afl++.json). + +## AFL++ metrics and StatsD + +StatsD allows you to receive and aggregate metrics from a wide range of +applications and retransmit them to a backend of your choice. + +From AFL++, StatsD can receive the following metrics: +- cur_path - cycle_done - cycles_wo_finds +- edges_found - execs_done - execs_per_sec -- paths_total +- havoc_expansion +- max_depth - paths_favored - paths_found - paths_imported -- max_depth -- cur_path +- paths_total - pending_favs - pending_total -- variable_paths +- slowest_exec_ms +- total_crashes - unique_crashes - unique_hangs -- total_crashes -- slowest_exec_ms -- edges_found - var_byte_count -- havoc_expansion +- variable_paths -Compared to the default integrated UI, these metrics give you the opportunity to visualize trends and fuzzing state over time. -By doing so, you might be able to see when the fuzzing process has reached a state of no progress, visualize what are the "best strategies" -(according to your own criteria) for your targets, etc. And doing so without requiring to log into each instance manually. +Depending on your StatsD server, you will be able to monitor, trigger alerts, or +perform actions based on these metrics (for example: alert on slow exec/s for a +new build, threshold of crashes, time since last crash > X, and so on). -An example visualisation may look like the following: - +## Setting environment variables in AFL++ -*Notes: The exact same dashboard can be imported with [this JSON template](resources/grafana-afl++.json).* +1. To enable the StatsD metrics collection on your fuzzer instances, set the + environment variable `AFL_STATSD=1`. By default, AFL++ will send the metrics + over UDP to 127.0.0.1:8125. -## How to use +2. To enable tags for each metric based on their format (banner and + afl_version), set the environment variable `AFL_STATSD_TAGS_FLAVOR`. By + default, no tags will be added to the metrics. -To enable the StatsD reporting on your fuzzer instances, you need to set the environment variable `AFL_STATSD=1`. + The available values are the following: + - `dogstatsd` + - `influxdb` + - `librato` + - `signalfx` -Setting `AFL_STATSD_TAGS_FLAVOR` to the provider of your choice will assign tags / labels to each metric based on their format. -The possible values are `dogstatsd`, `librato`, `signalfx` or `influxdb`. -For more information on these env vars, check out `docs/env_variables.md`. + For more information on environment variables, see + [env_variables.md](env_variables.md). -The simplest way of using this feature is to use any metric provider and change the host/port of your StatsD daemon, -with `AFL_STATSD_HOST` and `AFL_STATSD_PORT`, if required (defaults are `localhost` and port `8125`). -To get started, here are some instructions with free and open source tools. -The following setup is based on Prometheus, statsd_exporter and Grafana. -Grafana here is not mandatory, but gives you some nice graphs and features. + Note: When using multiple fuzzer instances with StatsD it is *strongly* + recommended to set up `AFL_STATSD_TAGS_FLAVOR` to match your StatsD server. + This will allow you to see individual fuzzer performance, detect bad ones, + and see the progress of each strategy. -Depending on your setup and infrastructure, you may want to run these applications not on your fuzzer instances. -Only one instance of these 3 application is required for all your fuzzers. +3. Optional: To set the host and port of your StatsD daemon, set + `AFL_STATSD_HOST` and `AFL_STATSD_PORT`. The default values are `localhost` + and `8125`. -To simplify everything, we will use Docker and docker-compose. -Make sure you have them both installed. On most common Linux distributions, it's as simple as: +## Installing and setting up StatsD, Prometheus, and Grafana -```sh -curl -fsSL https://get.docker.com -o get-docker.sh -sh get-docker.sh -``` +The easiest way to install and set up the infrastructure is with Docker and +Docker Compose. -Once that's done, we can create the infrastructure. -Create and move into the directory of your choice. This will store all the configurations files required. - -First, create a `docker-compose.yml` containing the following: -```yml -version: '3' - -networks: - statsd-net: - driver: bridge - -services: - prometheus: - image: prom/prometheus - container_name: prometheus - volumes: - - ./prometheus.yml:/prometheus.yml - command: - - '--config.file=/prometheus.yml' - restart: unless-stopped - ports: - - "9090:9090" - networks: - - statsd-net - - statsd_exporter: - image: prom/statsd-exporter - container_name: statsd_exporter - volumes: - - ./statsd_mapping.yml:/statsd_mapping.yml - command: - - "--statsd.mapping-config=/statsd_mapping.yml" - ports: - - "9102:9102/tcp" - - "8125:9125/udp" - networks: - - statsd-net - - grafana: - image: grafana/grafana - container_name: grafana - restart: unless-stopped - ports: - - "3000:3000" - networks: - - statsd-net -``` +Depending on your fuzzing setup and infrastructure, you may not want to run +these applications on your fuzzer instances. This setup may be modified before +use in a production environment; for example, adding passwords, creating volumes +for storage, tweaking the metrics gathering to get host metrics (CPU, RAM, and +so on). -Then `prometheus.yml` -```yml -global: - scrape_interval: 15s - evaluation_interval: 15s +For all your fuzzing instances, only one instance of Prometheus and Grafana is +required. The +[statsd exporter](https://registry.hub.docker.com/r/prom/statsd-exporter) +converts the StatsD metrics to Prometheus. If you are using a provider that +supports StatsD directly, you can skip this part of the setup." -scrape_configs: - - job_name: 'fuzzing_metrics' - static_configs: - - targets: ['statsd_exporter:9102'] -``` +You can create and move the infrastructure files into a directory of your +choice. The directory will store all the required configuration files. -And finally `statsd_mapping.yml` -```yml -mappings: -- match: "fuzzing.*" - name: "fuzzing" - labels: - type: "$1" -``` +To install and set up Prometheus and Grafana: + +1. Install Docker and Docker Compose: + + ```sh + curl -fsSL https://get.docker.com -o get-docker.sh + sh get-docker.sh + ``` -Run `docker-compose up -d`. +2. Create a `docker-compose.yml` containing the following: -Everything should now be setup, you are now able to run your fuzzers with + ```yml + version: '3' + + networks: + statsd-net: + driver: bridge + + services: + prometheus: + image: prom/prometheus + container_name: prometheus + volumes: + - ./prometheus.yml:/prometheus.yml + command: + - '--config.file=/prometheus.yml' + restart: unless-stopped + ports: + - "9090:9090" + networks: + - statsd-net + + statsd_exporter: + image: prom/statsd-exporter + container_name: statsd_exporter + volumes: + - ./statsd_mapping.yml:/statsd_mapping.yml + command: + - "--statsd.mapping-config=/statsd_mapping.yml" + ports: + - "9102:9102/tcp" + - "8125:9125/udp" + networks: + - statsd-net + + grafana: + image: grafana/grafana + container_name: grafana + restart: unless-stopped + ports: + - "3000:3000" + networks: + - statsd-net + ``` + +3. Create a `prometheus.yml` containing the following: + + ```yml + global: + scrape_interval: 15s + evaluation_interval: 15s + + scrape_configs: + - job_name: 'fuzzing_metrics' + static_configs: + - targets: ['statsd_exporter:9102'] + ``` + +4. Create a `statsd_mapping.yml` containing the following: + + ```yml + mappings: + - match: "fuzzing.*" + name: "fuzzing" + labels: + type: "$1" + ``` + +5. Run `docker-compose up -d`. + +## Running AFL++ with StatsD + +To run your fuzzing instances: ``` -AFL_STATSD_TAGS_FLAVOR=dogstatsd AFL_STATSD=1 afl-fuzz -M test-fuzzer-1 -i i -o o ./bin/my-application @@ -AFL_STATSD_TAGS_FLAVOR=dogstatsd AFL_STATSD=1 afl-fuzz -S test-fuzzer-2 -i i -o o ./bin/my-application @@ +AFL_STATSD_TAGS_FLAVOR=dogstatsd AFL_STATSD=1 afl-fuzz -M test-fuzzer-1 -i i -o o [./bin/my-application] @@ +AFL_STATSD_TAGS_FLAVOR=dogstatsd AFL_STATSD=1 afl-fuzz -S test-fuzzer-2 -i i -o o [./bin/my-application] @@ ... -``` - -This setup may be modified before use in a production environment. Depending on your needs: adding passwords, creating volumes for storage, -tweaking the metrics gathering to get host metrics (CPU, RAM ...). +``` \ No newline at end of file diff --git a/docs/sister_projects.md b/docs/sister_projects.md deleted file mode 100644 index 5cb3a102..00000000 --- a/docs/sister_projects.md +++ /dev/null @@ -1,319 +0,0 @@ -# Sister projects - -This doc lists some of the projects that are inspired by, derived from, -designed for, or meant to integrate with AFL. See README.md for the general -instruction manual. - -!!! -!!! This list is outdated and needs an update, missing: e.g. Angora, FairFuzz -!!! - -## Support for other languages / environments: - -### Python AFL (Jakub Wilk) - -Allows fuzz-testing of Python programs. Uses custom instrumentation and its -own forkserver. - -http://jwilk.net/software/python-afl - -### Go-fuzz (Dmitry Vyukov) - -AFL-inspired guided fuzzing approach for Go targets: - -https://github.com/dvyukov/go-fuzz - -### afl.rs (Keegan McAllister) - -Allows Rust features to be easily fuzzed with AFL (using the LLVM mode). - -https://github.com/kmcallister/afl.rs - -### OCaml support (KC Sivaramakrishnan) - -Adds AFL-compatible instrumentation to OCaml programs. - -https://github.com/ocamllabs/opam-repo-dev/pull/23 -http://canopy.mirage.io/Posts/Fuzzing - -### AFL for GCJ Java and other GCC frontends (-) - -GCC Java programs are actually supported out of the box - simply rename -afl-gcc to afl-gcj. Unfortunately, by default, unhandled exceptions in GCJ do -not result in abort() being called, so you will need to manually add a -top-level exception handler that exits with SIGABRT or something equivalent. - -Other GCC-supported languages should be fairly easy to get working, but may -face similar problems. See https://gcc.gnu.org/frontends.html for a list of -options. - -## AFL-style in-process fuzzer for LLVM (Kostya Serebryany) - -Provides an evolutionary instrumentation-guided fuzzing harness that allows -some programs to be fuzzed without the fork / execve overhead. (Similar -functionality is now available as the "persistent" feature described in -[the llvm_mode readme](../instrumentation/README.llvm.md)) - -http://llvm.org/docs/LibFuzzer.html - -## TriforceAFL (Tim Newsham and Jesse Hertz) - -Leverages QEMU full system emulation mode to allow AFL to target operating -systems and other alien worlds: - -https://www.nccgroup.trust/us/about-us/newsroom-and-events/blog/2016/june/project-triforce-run-afl-on-everything/ - -## WinAFL (Ivan Fratric) - -As the name implies, allows you to fuzz Windows binaries (using DynamoRio). - -https://github.com/ivanfratric/winafl - -Another Windows alternative may be: - -https://github.com/carlosgprado/BrundleFuzz/ - -## Network fuzzing - -### Preeny (Yan Shoshitaishvili) - -Provides a fairly simple way to convince dynamically linked network-centric -programs to read from a file or not fork. Not AFL-specific, but described as -useful by many users. Some assembly required. - -https://github.com/zardus/preeny - -## Distributed fuzzing and related automation - -### roving (Richo Healey) - -A client-server architecture for effortlessly orchestrating AFL runs across -a fleet of machines. You don't want to use this on systems that face the -Internet or live in other untrusted environments. - -https://github.com/richo/roving - -### Distfuzz-AFL (Martijn Bogaard) - -Simplifies the management of afl-fuzz instances on remote machines. The -author notes that the current implementation isn't secure and should not -be exposed on the Internet. - -https://github.com/MartijnB/disfuzz-afl - -### AFLDFF (quantumvm) - -A nice GUI for managing AFL jobs. - -https://github.com/quantumvm/AFLDFF - -### afl-launch (Ben Nagy) - -Batch AFL launcher utility with a simple CLI. - -https://github.com/bnagy/afl-launch - -### AFL Utils (rc0r) - -Simplifies the triage of discovered crashes, start parallel instances, etc. - -https://github.com/rc0r/afl-utils - -### AFL crash analyzer (floyd) - -Another crash triage tool: - -https://github.com/floyd-fuh/afl-crash-analyzer - -### afl-extras (fekir) - -Collect data, parallel afl-tmin, startup scripts. - -https://github.com/fekir/afl-extras - -### afl-fuzzing-scripts (Tobias Ospelt) - -Simplifies starting up multiple parallel AFL jobs. - -https://github.com/floyd-fuh/afl-fuzzing-scripts/ - -### afl-sid (Jacek Wielemborek) - -Allows users to more conveniently build and deploy AFL via Docker. - -https://github.com/d33tah/afl-sid - -Another Docker-related project: - -https://github.com/ozzyjohnson/docker-afl - -### afl-monitor (Paul S. Ziegler) - -Provides more detailed and versatile statistics about your running AFL jobs. - -https://github.com/reflare/afl-monitor - -### FEXM (Security in Telecommunications) - -Fully automated fuzzing framework, based on AFL - -https://github.com/fgsect/fexm - -## Crash triage, coverage analysis, and other companion tools: - -### afl-crash-analyzer (Tobias Ospelt) - -Makes it easier to navigate and annotate crashing test cases. - -https://github.com/floyd-fuh/afl-crash-analyzer/ - -### Crashwalk (Ben Nagy) - -AFL-aware tool to annotate and sort through crashing test cases. - -https://github.com/bnagy/crashwalk - -### afl-cov (Michael Rash) - -Produces human-readable coverage data based on the output queue of afl-fuzz. - -https://github.com/mrash/afl-cov - -### afl-sancov (Bhargava Shastry) - -Similar to afl-cov, but uses clang sanitizer instrumentation. - -https://github.com/bshastry/afl-sancov - -### RecidiVM (Jakub Wilk) - -Makes it easy to estimate memory usage limits when fuzzing with ASAN or MSAN. - -http://jwilk.net/software/recidivm - -### aflize (Jacek Wielemborek) - -Automatically build AFL-enabled versions of Debian packages. - -https://github.com/d33tah/aflize - -### afl-ddmin-mod (Markus Teufelberger) - -A variant of afl-tmin that uses a more sophisticated (but slower) -minimization algorithm. - -https://github.com/MarkusTeufelberger/afl-ddmin-mod - -### afl-kit (Kuang-che Wu) - -Replacements for afl-cmin and afl-tmin with additional features, such -as the ability to filter crashes based on stderr patterns. - -https://github.com/kcwu/afl-kit - -## Narrow-purpose or experimental: - -### Cygwin support (Ali Rizvi-Santiago) - -Pretty self-explanatory. As per the author, this "mostly" ports AFL to -Windows. Field reports welcome! - -https://github.com/arizvisa/afl-cygwin - -### Pause and resume scripts (Ben Nagy) - -Simple automation to suspend and resume groups of fuzzing jobs. - -https://github.com/bnagy/afl-trivia - -### Static binary-only instrumentation (Aleksandar Nikolich) - -Allows black-box binaries to be instrumented statically (i.e., by modifying -the binary ahead of the time, rather than translating it on the run). Author -reports better performance compared to QEMU, but occasional translation -errors with stripped binaries. - -https://github.com/vanhauser-thc/afl-dyninst - -### AFL PIN (Parker Thompson) - -Early-stage Intel PIN instrumentation support (from before we settled on -faster-running QEMU). - -https://github.com/mothran/aflpin - -### AFL-style instrumentation in llvm (Kostya Serebryany) - -Allows AFL-equivalent instrumentation to be injected at compiler level. -This is currently not supported by AFL as-is, but may be useful in other -projects. - -https://code.google.com/p/address-sanitizer/wiki/AsanCoverage#Coverage_counters - -### AFL JS (Han Choongwoo) - -One-off optimizations to speed up the fuzzing of JavaScriptCore (now likely -superseded by LLVM deferred forkserver init - see README.llvm.md). - -https://github.com/tunz/afl-fuzz-js - -### AFL harness for fwknop (Michael Rash) - -An example of a fairly involved integration with AFL. - -https://github.com/mrash/fwknop/tree/master/test/afl - -### Building harnesses for DNS servers (Jonathan Foote, Ron Bowes) - -Two articles outlining the general principles and showing some example code. - -https://www.fastly.com/blog/how-to-fuzz-server-american-fuzzy-lop -https://goo.gl/j9EgFf - -### Fuzzer shell for SQLite (Richard Hipp) - -A simple SQL shell designed specifically for fuzzing the underlying library. - -http://www.sqlite.org/src/artifact/9e7e273da2030371 - -### Support for Python mutation modules (Christian Holler) - -now integrated in AFL++, originally from here -https://github.com/choller/afl/blob/master/docs/mozilla/python_modules.txt - -### Support for selective instrumentation (Christian Holler) - -now integrated in AFL++, originally from here -https://github.com/choller/afl/blob/master/docs/mozilla/partial_instrumentation.txt - -### Syzkaller (Dmitry Vyukov) - -A similar guided approach as applied to fuzzing syscalls: - -https://github.com/google/syzkaller/wiki/Found-Bugs -https://github.com/dvyukov/linux/commit/33787098ffaaa83b8a7ccf519913ac5fd6125931 -http://events.linuxfoundation.org/sites/events/files/slides/AFL%20filesystem%20fuzzing%2C%20Vault%202016_0.pdf - - -### Kernel Snapshot Fuzzing using Unicornafl (Security in Telecommunications) - -https://github.com/fgsect/unicorefuzz - -### Android support (ele7enxxh) - -Based on a somewhat dated version of AFL: - -https://github.com/ele7enxxh/android-afl - -### CGI wrapper (floyd) - -Facilitates the testing of CGI scripts. - -https://github.com/floyd-fuh/afl-cgi-wrapper - -### Fuzzing difficulty estimation (Marcel Boehme) - -A fork of AFL that tries to quantify the likelihood of finding additional -paths or crashes at any point in a fuzzing job. - -https://github.com/mboehme/pythia diff --git a/docs/status_screen.md b/docs/status_screen.md deleted file mode 100644 index b1cb9696..00000000 --- a/docs/status_screen.md +++ /dev/null @@ -1,444 +0,0 @@ -# Understanding the status screen - -This document provides an overview of the status screen - plus tips for -troubleshooting any warnings and red text shown in the UI. See README.md for -the general instruction manual. - -## A note about colors - -The status screen and error messages use colors to keep things readable and -attract your attention to the most important details. For example, red almost -always means "consult this doc" :-) - -Unfortunately, the UI will render correctly only if your terminal is using -traditional un*x palette (white text on black background) or something close -to that. - -If you are using inverse video, you may want to change your settings, say: - -- For GNOME Terminal, go to `Edit > Profile` preferences, select the "colors" tab, and from the list of built-in schemes, choose "white on black". -- For the MacOS X Terminal app, open a new window using the "Pro" scheme via the `Shell > New Window` menu (or make "Pro" your default). - -Alternatively, if you really like your current colors, you can edit config.h -to comment out USE_COLORS, then do `make clean all`. - -I'm not aware of any other simple way to make this work without causing -other side effects - sorry about that. - -With that out of the way, let's talk about what's actually on the screen... - -### The status bar - -``` -american fuzzy lop ++3.01a (default) [fast] {0} -``` - -The top line shows you which mode afl-fuzz is running in -(normal: "american fuzy lop", crash exploration mode: "peruvian rabbit mode") -and the version of AFL++. -Next to the version is the banner, which, if not set with -T by hand, will -either show the binary name being fuzzed, or the -M/-S main/secondary name for -parallel fuzzing. -Second to last is the power schedule mode being run (default: fast). -Finally, the last item is the CPU id. - -### Process timing - -``` - +----------------------------------------------------+ - | run time : 0 days, 8 hrs, 32 min, 43 sec | - | last new path : 0 days, 0 hrs, 6 min, 40 sec | - | last uniq crash : none seen yet | - | last uniq hang : 0 days, 1 hrs, 24 min, 32 sec | - +----------------------------------------------------+ -``` - -This section is fairly self-explanatory: it tells you how long the fuzzer has -been running and how much time has elapsed since its most recent finds. This is -broken down into "paths" (a shorthand for test cases that trigger new execution -patterns), crashes, and hangs. - -When it comes to timing: there is no hard rule, but most fuzzing jobs should be -expected to run for days or weeks; in fact, for a moderately complex project, the -first pass will probably take a day or so. Every now and then, some jobs -will be allowed to run for months. - -There's one important thing to watch out for: if the tool is not finding new -paths within several minutes of starting, you're probably not invoking the -target binary correctly and it never gets to parse the input files we're -throwing at it; another possible explanations are that the default memory limit -(`-m`) is too restrictive, and the program exits after failing to allocate a -buffer very early on; or that the input files are patently invalid and always -fail a basic header check. - -If there are no new paths showing up for a while, you will eventually see a big -red warning in this section, too :-) - -### Overall results - -``` - +-----------------------+ - | cycles done : 0 | - | total paths : 2095 | - | uniq crashes : 0 | - | uniq hangs : 19 | - +-----------------------+ -``` - -The first field in this section gives you the count of queue passes done so far - that is, the number of times the fuzzer went over all the interesting test -cases discovered so far, fuzzed them, and looped back to the very beginning. -Every fuzzing session should be allowed to complete at least one cycle; and -ideally, should run much longer than that. - -As noted earlier, the first pass can take a day or longer, so sit back and -relax. - -To help make the call on when to hit `Ctrl-C`, the cycle counter is color-coded. -It is shown in magenta during the first pass, progresses to yellow if new finds -are still being made in subsequent rounds, then blue when that ends - and -finally, turns green after the fuzzer hasn't been seeing any action for a -longer while. - -The remaining fields in this part of the screen should be pretty obvious: -there's the number of test cases ("paths") discovered so far, and the number of -unique faults. The test cases, crashes, and hangs can be explored in real-time -by browsing the output directory, as discussed in README.md. - -### Cycle progress - -``` - +-------------------------------------+ - | now processing : 1296 (61.86%) | - | paths timed out : 0 (0.00%) | - +-------------------------------------+ -``` - -This box tells you how far along the fuzzer is with the current queue cycle: it -shows the ID of the test case it is currently working on, plus the number of -inputs it decided to ditch because they were persistently timing out. - -The "*" suffix sometimes shown in the first line means that the currently -processed path is not "favored" (a property discussed later on). - -### Map coverage - -``` - +--------------------------------------+ - | map density : 10.15% / 29.07% | - | count coverage : 4.03 bits/tuple | - +--------------------------------------+ -``` - -The section provides some trivia about the coverage observed by the -instrumentation embedded in the target binary. - -The first line in the box tells you how many branch tuples we have already -hit, in proportion to how much the bitmap can hold. The number on the left -describes the current input; the one on the right is the value for the entire -input corpus. - -Be wary of extremes: - - - Absolute numbers below 200 or so suggest one of three things: that the - program is extremely simple; that it is not instrumented properly (e.g., - due to being linked against a non-instrumented copy of the target - library); or that it is bailing out prematurely on your input test cases. - The fuzzer will try to mark this in pink, just to make you aware. - - Percentages over 70% may very rarely happen with very complex programs - that make heavy use of template-generated code. - Because high bitmap density makes it harder for the fuzzer to reliably - discern new program states, I recommend recompiling the binary with - `AFL_INST_RATIO=10` or so and trying again (see env_variables.md). - The fuzzer will flag high percentages in red. Chances are, you will never - see that unless you're fuzzing extremely hairy software (say, v8, perl, - ffmpeg). - -The other line deals with the variability in tuple hit counts seen in the -binary. In essence, if every taken branch is always taken a fixed number of -times for all the inputs we have tried, this will read `1.00`. As we manage -to trigger other hit counts for every branch, the needle will start to move -toward `8.00` (every bit in the 8-bit map hit), but will probably never -reach that extreme. - -Together, the values can be useful for comparing the coverage of several -different fuzzing jobs that rely on the same instrumented binary. - -### Stage progress - -``` - +-------------------------------------+ - | now trying : interest 32/8 | - | stage execs : 3996/34.4k (11.62%) | - | total execs : 27.4M | - | exec speed : 891.7/sec | - +-------------------------------------+ -``` - -This part gives you an in-depth peek at what the fuzzer is actually doing right -now. It tells you about the current stage, which can be any of: - - - calibration - a pre-fuzzing stage where the execution path is examined - to detect anomalies, establish baseline execution speed, and so on. Executed - very briefly whenever a new find is being made. - - trim L/S - another pre-fuzzing stage where the test case is trimmed to the - shortest form that still produces the same execution path. The length (L) - and stepover (S) are chosen in general relationship to file size. - - bitflip L/S - deterministic bit flips. There are L bits toggled at any given - time, walking the input file with S-bit increments. The current L/S variants - are: `1/1`, `2/1`, `4/1`, `8/8`, `16/8`, `32/8`. - - arith L/8 - deterministic arithmetics. The fuzzer tries to subtract or add - small integers to 8-, 16-, and 32-bit values. The stepover is always 8 bits. - - interest L/8 - deterministic value overwrite. The fuzzer has a list of known - "interesting" 8-, 16-, and 32-bit values to try. The stepover is 8 bits. - - extras - deterministic injection of dictionary terms. This can be shown as - "user" or "auto", depending on whether the fuzzer is using a user-supplied - dictionary (`-x`) or an auto-created one. You will also see "over" or "insert", - depending on whether the dictionary words overwrite existing data or are - inserted by offsetting the remaining data to accommodate their length. - - havoc - a sort-of-fixed-length cycle with stacked random tweaks. The - operations attempted during this stage include bit flips, overwrites with - random and "interesting" integers, block deletion, block duplication, plus - assorted dictionary-related operations (if a dictionary is supplied in the - first place). - - splice - a last-resort strategy that kicks in after the first full queue - cycle with no new paths. It is equivalent to 'havoc', except that it first - splices together two random inputs from the queue at some arbitrarily - selected midpoint. - - sync - a stage used only when `-M` or `-S` is set (see parallel_fuzzing.md). - No real fuzzing is involved, but the tool scans the output from other - fuzzers and imports test cases as necessary. The first time this is done, - it may take several minutes or so. - -The remaining fields should be fairly self-evident: there's the exec count -progress indicator for the current stage, a global exec counter, and a -benchmark for the current program execution speed. This may fluctuate from -one test case to another, but the benchmark should be ideally over 500 execs/sec -most of the time - and if it stays below 100, the job will probably take very -long. - -The fuzzer will explicitly warn you about slow targets, too. If this happens, -see the [perf_tips.md](perf_tips.md) file included with the fuzzer for ideas on how to speed -things up. - -### Findings in depth - -``` - +--------------------------------------+ - | favored paths : 879 (41.96%) | - | new edges on : 423 (20.19%) | - | total crashes : 0 (0 unique) | - | total tmouts : 24 (19 unique) | - +--------------------------------------+ -``` - -This gives you several metrics that are of interest mostly to complete nerds. -The section includes the number of paths that the fuzzer likes the most based -on a minimization algorithm baked into the code (these will get considerably -more air time), and the number of test cases that actually resulted in better -edge coverage (versus just pushing the branch hit counters up). There are also -additional, more detailed counters for crashes and timeouts. - -Note that the timeout counter is somewhat different from the hang counter; this -one includes all test cases that exceeded the timeout, even if they did not -exceed it by a margin sufficient to be classified as hangs. - -### Fuzzing strategy yields - -``` - +-----------------------------------------------------+ - | bit flips : 57/289k, 18/289k, 18/288k | - | byte flips : 0/36.2k, 4/35.7k, 7/34.6k | - | arithmetics : 53/2.54M, 0/537k, 0/55.2k | - | known ints : 8/322k, 12/1.32M, 10/1.70M | - | dictionary : 9/52k, 1/53k, 1/24k | - |havoc/splice : 1903/20.0M, 0/0 | - |py/custom/rq : unused, 53/2.54M, unused | - | trim/eff : 20.31%/9201, 17.05% | - +-----------------------------------------------------+ -``` - -This is just another nerd-targeted section keeping track of how many paths we -have netted, in proportion to the number of execs attempted, for each of the -fuzzing strategies discussed earlier on. This serves to convincingly validate -assumptions about the usefulness of the various approaches taken by afl-fuzz. - -The trim strategy stats in this section are a bit different than the rest. -The first number in this line shows the ratio of bytes removed from the input -files; the second one corresponds to the number of execs needed to achieve this -goal. Finally, the third number shows the proportion of bytes that, although -not possible to remove, were deemed to have no effect and were excluded from -some of the more expensive deterministic fuzzing steps. - -Note that when deterministic mutation mode is off (which is the default -because it is not very efficient) the first five lines display -"disabled (default, enable with -D)". - -Only what is activated will have counter shown. - -### Path geometry - -``` - +---------------------+ - | levels : 5 | - | pending : 1570 | - | pend fav : 583 | - | own finds : 0 | - | imported : 0 | - | stability : 100.00% | - +---------------------+ -``` - -The first field in this section tracks the path depth reached through the -guided fuzzing process. In essence: the initial test cases supplied by the -user are considered "level 1". The test cases that can be derived from that -through traditional fuzzing are considered "level 2"; the ones derived by -using these as inputs to subsequent fuzzing rounds are "level 3"; and so forth. -The maximum depth is therefore a rough proxy for how much value you're getting -out of the instrumentation-guided approach taken by afl-fuzz. - -The next field shows you the number of inputs that have not gone through any -fuzzing yet. The same stat is also given for "favored" entries that the fuzzer -really wants to get to in this queue cycle (the non-favored entries may have to -wait a couple of cycles to get their chance). - -Next, we have the number of new paths found during this fuzzing section and -imported from other fuzzer instances when doing parallelized fuzzing; and the -extent to which identical inputs appear to sometimes produce variable behavior -in the tested binary. - -That last bit is actually fairly interesting: it measures the consistency of -observed traces. If a program always behaves the same for the same input data, -it will earn a score of 100%. When the value is lower but still shown in purple, -the fuzzing process is unlikely to be negatively affected. If it goes into red, -you may be in trouble, since AFL will have difficulty discerning between -meaningful and "phantom" effects of tweaking the input file. - -Now, most targets will just get a 100% score, but when you see lower figures, -there are several things to look at: - - - The use of uninitialized memory in conjunction with some intrinsic sources - of entropy in the tested binary. Harmless to AFL, but could be indicative - of a security bug. - - Attempts to manipulate persistent resources, such as left over temporary - files or shared memory objects. This is usually harmless, but you may want - to double-check to make sure the program isn't bailing out prematurely. - Running out of disk space, SHM handles, or other global resources can - trigger this, too. - - Hitting some functionality that is actually designed to behave randomly. - Generally harmless. For example, when fuzzing sqlite, an input like - `select random();` will trigger a variable execution path. - - Multiple threads executing at once in semi-random order. This is harmless - when the 'stability' metric stays over 90% or so, but can become an issue - if not. Here's what to try: - * Use afl-clang-fast from [instrumentation](../instrumentation/) - it uses a thread-local tracking - model that is less prone to concurrency issues, - * See if the target can be compiled or run without threads. Common - `./configure` options include `--without-threads`, `--disable-pthreads`, or - `--disable-openmp`. - * Replace pthreads with GNU Pth (https://www.gnu.org/software/pth/), which - allows you to use a deterministic scheduler. - - In persistent mode, minor drops in the "stability" metric can be normal, - because not all the code behaves identically when re-entered; but major - dips may signify that the code within `__AFL_LOOP()` is not behaving - correctly on subsequent iterations (e.g., due to incomplete clean-up or - reinitialization of the state) and that most of the fuzzing effort goes - to waste. - -The paths where variable behavior is detected are marked with a matching entry -in the `<out_dir>/queue/.state/variable_behavior/` directory, so you can look -them up easily. - -### CPU load - -``` - [cpu: 25%] -``` - -This tiny widget shows the apparent CPU utilization on the local system. It is -calculated by taking the number of processes in the "runnable" state, and then -comparing it to the number of logical cores on the system. - -If the value is shown in green, you are using fewer CPU cores than available on -your system and can probably parallelize to improve performance; for tips on -how to do that, see parallel_fuzzing.md. - -If the value is shown in red, your CPU is *possibly* oversubscribed, and -running additional fuzzers may not give you any benefits. - -Of course, this benchmark is very simplistic; it tells you how many processes -are ready to run, but not how resource-hungry they may be. It also doesn't -distinguish between physical cores, logical cores, and virtualized CPUs; the -performance characteristics of each of these will differ quite a bit. - -If you want a more accurate measurement, you can run the `afl-gotcpu` utility from the command line. - -### Addendum: status and plot files - -For unattended operation, some of the key status screen information can be also -found in a machine-readable format in the fuzzer_stats file in the output -directory. This includes: - - - `start_time` - unix time indicating the start time of afl-fuzz - - `last_update` - unix time corresponding to the last update of this file - - `run_time` - run time in seconds to the last update of this file - - `fuzzer_pid` - PID of the fuzzer process - - `cycles_done` - queue cycles completed so far - - `cycles_wo_finds` - number of cycles without any new paths found - - `execs_done` - number of execve() calls attempted - - `execs_per_sec` - overall number of execs per second - - `paths_total` - total number of entries in the queue - - `paths_favored` - number of queue entries that are favored - - `paths_found` - number of entries discovered through local fuzzing - - `paths_imported` - number of entries imported from other instances - - `max_depth` - number of levels in the generated data set - - `cur_path` - currently processed entry number - - `pending_favs` - number of favored entries still waiting to be fuzzed - - `pending_total` - number of all entries waiting to be fuzzed - - `variable_paths` - number of test cases showing variable behavior - - `stability` - percentage of bitmap bytes that behave consistently - - `bitmap_cvg` - percentage of edge coverage found in the map so far - - `unique_crashes` - number of unique crashes recorded - - `unique_hangs` - number of unique hangs encountered - - `last_path` - seconds since the last path was found - - `last_crash` - seconds since the last crash was found - - `last_hang` - seconds since the last hang was found - - `execs_since_crash` - execs since the last crash was found - - `exec_timeout` - the -t command line value - - `slowest_exec_ms` - real time of the slowest execution in ms - - `peak_rss_mb` - max rss usage reached during fuzzing in MB - - `edges_found` - how many edges have been found - - `var_byte_count` - how many edges are non-deterministic - - `afl_banner` - banner text (e.g. the target name) - - `afl_version` - the version of AFL used - - `target_mode` - default, persistent, qemu, unicorn, non-instrumented - - `command_line` - full command line used for the fuzzing session - -Most of these map directly to the UI elements discussed earlier on. - -On top of that, you can also find an entry called `plot_data`, containing a -plottable history for most of these fields. If you have gnuplot installed, you -can turn this into a nice progress report with the included `afl-plot` tool. - - -### Addendum: Automatically send metrics with StatsD - -In a CI environment or when running multiple fuzzers, it can be tedious to -log into each of them or deploy scripts to read the fuzzer statistics. -Using `AFL_STATSD` (and the other related environment variables `AFL_STATSD_HOST`, -`AFL_STATSD_PORT`, `AFL_STATSD_TAGS_FLAVOR`) you can automatically send metrics -to your favorite StatsD server. Depending on your StatsD server you will be able -to monitor, trigger alerts or perform actions based on these metrics (e.g: alert on -slow exec/s for a new build, threshold of crashes, time since last crash > X, etc). - -The selected metrics are a subset of all the metrics found in the status and in -the plot file. The list is the following: `cycle_done`, `cycles_wo_finds`, -`execs_done`,`execs_per_sec`, `paths_total`, `paths_favored`, `paths_found`, -`paths_imported`, `max_depth`, `cur_path`, `pending_favs`, `pending_total`, -`variable_paths`, `unique_crashes`, `unique_hangs`, `total_crashes`, -`slowest_exec_ms`, `edges_found`, `var_byte_count`, `havoc_expansion`. -Their definitions can be found in the addendum above. - -When using multiple fuzzer instances with StatsD it is *strongly* recommended to setup -the flavor (AFL_STATSD_TAGS_FLAVOR) to match your StatsD server. This will allow you -to see individual fuzzer performance, detect bad ones, see the progress of each -strategy... diff --git a/docs/technical_details.md b/docs/technical_details.md deleted file mode 100644 index b0ca493e..00000000 --- a/docs/technical_details.md +++ /dev/null @@ -1,550 +0,0 @@ -# Technical "whitepaper" for afl-fuzz - - -NOTE: this document is rather outdated! - - -This document provides a quick overview of the guts of American Fuzzy Lop. -See README.md for the general instruction manual; and for a discussion of -motivations and design goals behind AFL, see historical_notes.md. - -## 0. Design statement - -American Fuzzy Lop does its best not to focus on any singular principle of -operation and not be a proof-of-concept for any specific theory. The tool can -be thought of as a collection of hacks that have been tested in practice, -found to be surprisingly effective, and have been implemented in the simplest, -most robust way I could think of at the time. - -Many of the resulting features are made possible thanks to the availability of -lightweight instrumentation that served as a foundation for the tool, but this -mechanism should be thought of merely as a means to an end. The only true -governing principles are speed, reliability, and ease of use. - -## 1. Coverage measurements - -The instrumentation injected into compiled programs captures branch (edge) -coverage, along with coarse branch-taken hit counts. The code injected at -branch points is essentially equivalent to: - -```c - cur_location = <COMPILE_TIME_RANDOM>; - shared_mem[cur_location ^ prev_location]++; - prev_location = cur_location >> 1; -``` - -The `cur_location` value is generated randomly to simplify the process of -linking complex projects and keep the XOR output distributed uniformly. - -The `shared_mem[]` array is a 64 kB SHM region passed to the instrumented binary -by the caller. Every byte set in the output map can be thought of as a hit for -a particular (`branch_src`, `branch_dst`) tuple in the instrumented code. - -The size of the map is chosen so that collisions are sporadic with almost all -of the intended targets, which usually sport between 2k and 10k discoverable -branch points: - -``` - Branch cnt | Colliding tuples | Example targets - ------------+------------------+----------------- - 1,000 | 0.75% | giflib, lzo - 2,000 | 1.5% | zlib, tar, xz - 5,000 | 3.5% | libpng, libwebp - 10,000 | 7% | libxml - 20,000 | 14% | sqlite - 50,000 | 30% | - -``` - -At the same time, its size is small enough to allow the map to be analyzed -in a matter of microseconds on the receiving end, and to effortlessly fit -within L2 cache. - -This form of coverage provides considerably more insight into the execution -path of the program than simple block coverage. In particular, it trivially -distinguishes between the following execution traces: - -``` - A -> B -> C -> D -> E (tuples: AB, BC, CD, DE) - A -> B -> D -> C -> E (tuples: AB, BD, DC, CE) -``` - -This aids the discovery of subtle fault conditions in the underlying code, -because security vulnerabilities are more often associated with unexpected -or incorrect state transitions than with merely reaching a new basic block. - -The reason for the shift operation in the last line of the pseudocode shown -earlier in this section is to preserve the directionality of tuples (without -this, A ^ B would be indistinguishable from B ^ A) and to retain the identity -of tight loops (otherwise, A ^ A would be obviously equal to B ^ B). - -The absence of simple saturating arithmetic opcodes on Intel CPUs means that -the hit counters can sometimes wrap around to zero. Since this is a fairly -unlikely and localized event, it's seen as an acceptable performance trade-off. - -### 2. Detecting new behaviors - -The fuzzer maintains a global map of tuples seen in previous executions; this -data can be rapidly compared with individual traces and updated in just a couple -of dword- or qword-wide instructions and a simple loop. - -When a mutated input produces an execution trace containing new tuples, the -corresponding input file is preserved and routed for additional processing -later on (see section #3). Inputs that do not trigger new local-scale state -transitions in the execution trace (i.e., produce no new tuples) are discarded, -even if their overall control flow sequence is unique. - -This approach allows for a very fine-grained and long-term exploration of -program state while not having to perform any computationally intensive and -fragile global comparisons of complex execution traces, and while avoiding the -scourge of path explosion. - -To illustrate the properties of the algorithm, consider that the second trace -shown below would be considered substantially new because of the presence of -new tuples (CA, AE): - -``` - #1: A -> B -> C -> D -> E - #2: A -> B -> C -> A -> E -``` - -At the same time, with #2 processed, the following pattern will not be seen -as unique, despite having a markedly different overall execution path: - -``` - #3: A -> B -> C -> A -> B -> C -> A -> B -> C -> D -> E -``` - -In addition to detecting new tuples, the fuzzer also considers coarse tuple -hit counts. These are divided into several buckets: - -``` - 1, 2, 3, 4-7, 8-15, 16-31, 32-127, 128+ -``` - -To some extent, the number of buckets is an implementation artifact: it allows -an in-place mapping of an 8-bit counter generated by the instrumentation to -an 8-position bitmap relied on by the fuzzer executable to keep track of the -already-seen execution counts for each tuple. - -Changes within the range of a single bucket are ignored; transition from one -bucket to another is flagged as an interesting change in program control flow, -and is routed to the evolutionary process outlined in the section below. - -The hit count behavior provides a way to distinguish between potentially -interesting control flow changes, such as a block of code being executed -twice when it was normally hit only once. At the same time, it is fairly -insensitive to empirically less notable changes, such as a loop going from -47 cycles to 48. The counters also provide some degree of "accidental" -immunity against tuple collisions in dense trace maps. - -The execution is policed fairly heavily through memory and execution time -limits; by default, the timeout is set at 5x the initially-calibrated -execution speed, rounded up to 20 ms. The aggressive timeouts are meant to -prevent dramatic fuzzer performance degradation by descending into tarpits -that, say, improve coverage by 1% while being 100x slower; we pragmatically -reject them and hope that the fuzzer will find a less expensive way to reach -the same code. Empirical testing strongly suggests that more generous time -limits are not worth the cost. - -## 3. Evolving the input queue - -Mutated test cases that produced new state transitions within the program are -added to the input queue and used as a starting point for future rounds of -fuzzing. They supplement, but do not automatically replace, existing finds. - -In contrast to more greedy genetic algorithms, this approach allows the tool -to progressively explore various disjoint and possibly mutually incompatible -features of the underlying data format, as shown in this image: - -  - -Several practical examples of the results of this algorithm are discussed -here: - - http://lcamtuf.blogspot.com/2014/11/pulling-jpegs-out-of-thin-air.html - http://lcamtuf.blogspot.com/2014/11/afl-fuzz-nobody-expects-cdata-sections.html - -The synthetic corpus produced by this process is essentially a compact -collection of "hmm, this does something new!" input files, and can be used to -seed any other testing processes down the line (for example, to manually -stress-test resource-intensive desktop apps). - -With this approach, the queue for most targets grows to somewhere between 1k -and 10k entries; approximately 10-30% of this is attributable to the discovery -of new tuples, and the remainder is associated with changes in hit counts. - -The following table compares the relative ability to discover file syntax and -explore program states when using several different approaches to guided -fuzzing. The instrumented target was GNU patch 2.7k.3 compiled with `-O3` and -seeded with a dummy text file; the session consisted of a single pass over the -input queue with afl-fuzz: - -``` - Fuzzer guidance | Blocks | Edges | Edge hit | Highest-coverage - strategy used | reached | reached | cnt var | test case generated - ------------------+---------+---------+----------+--------------------------- - (Initial file) | 156 | 163 | 1.00 | (none) - | | | | - Blind fuzzing S | 182 | 205 | 2.23 | First 2 B of RCS diff - Blind fuzzing L | 228 | 265 | 2.23 | First 4 B of -c mode diff - Block coverage | 855 | 1,130 | 1.57 | Almost-valid RCS diff - Edge coverage | 1,452 | 2,070 | 2.18 | One-chunk -c mode diff - AFL model | 1,765 | 2,597 | 4.99 | Four-chunk -c mode diff -``` - -The first entry for blind fuzzing ("S") corresponds to executing just a single -round of testing; the second set of figures ("L") shows the fuzzer running in a -loop for a number of execution cycles comparable with that of the instrumented -runs, which required more time to fully process the growing queue. - -Roughly similar results have been obtained in a separate experiment where the -fuzzer was modified to compile out all the random fuzzing stages and leave just -a series of rudimentary, sequential operations such as walking bit flips. -Because this mode would be incapable of altering the size of the input file, -the sessions were seeded with a valid unified diff: - -``` - Queue extension | Blocks | Edges | Edge hit | Number of unique - strategy used | reached | reached | cnt var | crashes found - ------------------+---------+---------+----------+------------------ - (Initial file) | 624 | 717 | 1.00 | - - | | | | - Blind fuzzing | 1,101 | 1,409 | 1.60 | 0 - Block coverage | 1,255 | 1,649 | 1.48 | 0 - Edge coverage | 1,259 | 1,734 | 1.72 | 0 - AFL model | 1,452 | 2,040 | 3.16 | 1 -``` - -At noted earlier on, some of the prior work on genetic fuzzing relied on -maintaining a single test case and evolving it to maximize coverage. At least -in the tests described above, this "greedy" approach appears to confer no -substantial benefits over blind fuzzing strategies. - -### 4. Culling the corpus - -The progressive state exploration approach outlined above means that some of -the test cases synthesized later on in the game may have edge coverage that -is a strict superset of the coverage provided by their ancestors. - -To optimize the fuzzing effort, AFL periodically re-evaluates the queue using a -fast algorithm that selects a smaller subset of test cases that still cover -every tuple seen so far, and whose characteristics make them particularly -favorable to the tool. - -The algorithm works by assigning every queue entry a score proportional to its -execution latency and file size; and then selecting lowest-scoring candidates -for each tuple. - -The tuples are then processed sequentially using a simple workflow: - - 1) Find next tuple not yet in the temporary working set, - 2) Locate the winning queue entry for this tuple, - 3) Register *all* tuples present in that entry's trace in the working set, - 4) Go to #1 if there are any missing tuples in the set. - -The generated corpus of "favored" entries is usually 5-10x smaller than the -starting data set. Non-favored entries are not discarded, but they are skipped -with varying probabilities when encountered in the queue: - - - If there are new, yet-to-be-fuzzed favorites present in the queue, 99% - of non-favored entries will be skipped to get to the favored ones. - - If there are no new favorites: - * If the current non-favored entry was fuzzed before, it will be skipped - 95% of the time. - * If it hasn't gone through any fuzzing rounds yet, the odds of skipping - drop down to 75%. - -Based on empirical testing, this provides a reasonable balance between queue -cycling speed and test case diversity. - -Slightly more sophisticated but much slower culling can be performed on input -or output corpora with `afl-cmin`. This tool permanently discards the redundant -entries and produces a smaller corpus suitable for use with `afl-fuzz` or -external tools. - -## 5. Trimming input files - -File size has a dramatic impact on fuzzing performance, both because large -files make the target binary slower, and because they reduce the likelihood -that a mutation would touch important format control structures, rather than -redundant data blocks. This is discussed in more detail in perf_tips.md. - -The possibility that the user will provide a low-quality starting corpus aside, -some types of mutations can have the effect of iteratively increasing the size -of the generated files, so it is important to counter this trend. - -Luckily, the instrumentation feedback provides a simple way to automatically -trim down input files while ensuring that the changes made to the files have no -impact on the execution path. - -The built-in trimmer in afl-fuzz attempts to sequentially remove blocks of data -with variable length and stepover; any deletion that doesn't affect the checksum -of the trace map is committed to disk. The trimmer is not designed to be -particularly thorough; instead, it tries to strike a balance between precision -and the number of `execve()` calls spent on the process, selecting the block size -and stepover to match. The average per-file gains are around 5-20%. - -The standalone `afl-tmin` tool uses a more exhaustive, iterative algorithm, and -also attempts to perform alphabet normalization on the trimmed files. The -operation of `afl-tmin` is as follows. - -First, the tool automatically selects the operating mode. If the initial input -crashes the target binary, afl-tmin will run in non-instrumented mode, simply -keeping any tweaks that produce a simpler file but still crash the target. -The same mode is used for hangs, if `-H` (hang mode) is specified. -If the target is non-crashing, the tool uses an instrumented mode and keeps only -the tweaks that produce exactly the same execution path. - -The actual minimization algorithm is: - - 1) Attempt to zero large blocks of data with large stepovers. Empirically, - this is shown to reduce the number of execs by preempting finer-grained - efforts later on. - 2) Perform a block deletion pass with decreasing block sizes and stepovers, - binary-search-style. - 3) Perform alphabet normalization by counting unique characters and trying - to bulk-replace each with a zero value. - 4) As a last result, perform byte-by-byte normalization on non-zero bytes. - -Instead of zeroing with a 0x00 byte, `afl-tmin` uses the ASCII digit '0'. This -is done because such a modification is much less likely to interfere with -text parsing, so it is more likely to result in successful minimization of -text files. - -The algorithm used here is less involved than some other test case -minimization approaches proposed in academic work, but requires far fewer -executions and tends to produce comparable results in most real-world -applications. - -## 6. Fuzzing strategies - -The feedback provided by the instrumentation makes it easy to understand the -value of various fuzzing strategies and optimize their parameters so that they -work equally well across a wide range of file types. The strategies used by -afl-fuzz are generally format-agnostic and are discussed in more detail here: - - http://lcamtuf.blogspot.com/2014/08/binary-fuzzing-strategies-what-works.html - -It is somewhat notable that especially early on, most of the work done by -`afl-fuzz` is actually highly deterministic, and progresses to random stacked -modifications and test case splicing only at a later stage. The deterministic -strategies include: - - - Sequential bit flips with varying lengths and stepovers, - - Sequential addition and subtraction of small integers, - - Sequential insertion of known interesting integers (`0`, `1`, `INT_MAX`, etc), - -The purpose of opening with deterministic steps is related to their tendency to -produce compact test cases and small diffs between the non-crashing and crashing -inputs. - -With deterministic fuzzing out of the way, the non-deterministic steps include -stacked bit flips, insertions, deletions, arithmetics, and splicing of different -test cases. - -The relative yields and `execve()` costs of all these strategies have been -investigated and are discussed in the aforementioned blog post. - -For the reasons discussed in historical_notes.md (chiefly, performance, -simplicity, and reliability), AFL generally does not try to reason about the -relationship between specific mutations and program states; the fuzzing steps -are nominally blind, and are guided only by the evolutionary design of the -input queue. - -That said, there is one (trivial) exception to this rule: when a new queue -entry goes through the initial set of deterministic fuzzing steps, and tweaks to -some regions in the file are observed to have no effect on the checksum of the -execution path, they may be excluded from the remaining phases of -deterministic fuzzing - and the fuzzer may proceed straight to random tweaks. -Especially for verbose, human-readable data formats, this can reduce the number -of execs by 10-40% or so without an appreciable drop in coverage. In extreme -cases, such as normally block-aligned tar archives, the gains can be as high as -90%. - -Because the underlying "effector maps" are local every queue entry and remain -in force only during deterministic stages that do not alter the size or the -general layout of the underlying file, this mechanism appears to work very -reliably and proved to be simple to implement. - -## 7. Dictionaries - -The feedback provided by the instrumentation makes it easy to automatically -identify syntax tokens in some types of input files, and to detect that certain -combinations of predefined or auto-detected dictionary terms constitute a -valid grammar for the tested parser. - -A discussion of how these features are implemented within afl-fuzz can be found -here: - - http://lcamtuf.blogspot.com/2015/01/afl-fuzz-making-up-grammar-with.html - -In essence, when basic, typically easily-obtained syntax tokens are combined -together in a purely random manner, the instrumentation and the evolutionary -design of the queue together provide a feedback mechanism to differentiate -between meaningless mutations and ones that trigger new behaviors in the -instrumented code - and to incrementally build more complex syntax on top of -this discovery. - -The dictionaries have been shown to enable the fuzzer to rapidly reconstruct -the grammar of highly verbose and complex languages such as JavaScript, SQL, -or XML; several examples of generated SQL statements are given in the blog -post mentioned above. - -Interestingly, the AFL instrumentation also allows the fuzzer to automatically -isolate syntax tokens already present in an input file. It can do so by looking -for run of bytes that, when flipped, produce a consistent change to the -program's execution path; this is suggestive of an underlying atomic comparison -to a predefined value baked into the code. The fuzzer relies on this signal -to build compact "auto dictionaries" that are then used in conjunction with -other fuzzing strategies. - -## 8. De-duping crashes - -De-duplication of crashes is one of the more important problems for any -competent fuzzing tool. Many of the naive approaches run into problems; in -particular, looking just at the faulting address may lead to completely -unrelated issues being clustered together if the fault happens in a common -library function (say, `strcmp`, `strcpy`); while checksumming call stack -backtraces can lead to extreme crash count inflation if the fault can be -reached through a number of different, possibly recursive code paths. - -The solution implemented in `afl-fuzz` considers a crash unique if any of two -conditions are met: - - - The crash trace includes a tuple not seen in any of the previous crashes, - - The crash trace is missing a tuple that was always present in earlier - faults. - -The approach is vulnerable to some path count inflation early on, but exhibits -a very strong self-limiting effect, similar to the execution path analysis -logic that is the cornerstone of `afl-fuzz`. - -## 9. Investigating crashes - -The exploitability of many types of crashes can be ambiguous; afl-fuzz tries -to address this by providing a crash exploration mode where a known-faulting -test case is fuzzed in a manner very similar to the normal operation of the -fuzzer, but with a constraint that causes any non-crashing mutations to be -thrown away. - -A detailed discussion of the value of this approach can be found here: - - http://lcamtuf.blogspot.com/2014/11/afl-fuzz-crash-exploration-mode.html - -The method uses instrumentation feedback to explore the state of the crashing -program to get past the ambiguous faulting condition and then isolate the -newly-found inputs for human review. - -On the subject of crashes, it is worth noting that in contrast to normal -queue entries, crashing inputs are *not* trimmed; they are kept exactly as -discovered to make it easier to compare them to the parent, non-crashing entry -in the queue. That said, `afl-tmin` can be used to shrink them at will. - -## 10 The fork server - -To improve performance, `afl-fuzz` uses a "fork server", where the fuzzed process -goes through `execve()`, linking, and libc initialization only once, and is then -cloned from a stopped process image by leveraging copy-on-write. The -implementation is described in more detail here: - - http://lcamtuf.blogspot.com/2014/10/fuzzing-binaries-without-execve.html - -The fork server is an integral aspect of the injected instrumentation and -simply stops at the first instrumented function to await commands from -`afl-fuzz`. - -With fast targets, the fork server can offer considerable performance gains, -usually between 1.5x and 2x. It is also possible to: - - - Use the fork server in manual ("deferred") mode, skipping over larger, - user-selected chunks of initialization code. It requires very modest - code changes to the targeted program, and With some targets, can - produce 10x+ performance gains. - - Enable "persistent" mode, where a single process is used to try out - multiple inputs, greatly limiting the overhead of repetitive `fork()` - calls. This generally requires some code changes to the targeted program, - but can improve the performance of fast targets by a factor of 5 or more - approximating the benefits of in-process fuzzing jobs while still - maintaining very robust isolation between the fuzzer process and the - targeted binary. - -## 11. Parallelization - -The parallelization mechanism relies on periodically examining the queues -produced by independently-running instances on other CPU cores or on remote -machines, and then selectively pulling in the test cases that, when tried -out locally, produce behaviors not yet seen by the fuzzer at hand. - -This allows for extreme flexibility in fuzzer setup, including running synced -instances against different parsers of a common data format, often with -synergistic effects. - -For more information about this design, see parallel_fuzzing.md. - -## 12. Binary-only instrumentation - -Instrumentation of black-box, binary-only targets is accomplished with the -help of a separately-built version of QEMU in "user emulation" mode. This also -allows the execution of cross-architecture code - say, ARM binaries on x86. - -QEMU uses basic blocks as translation units; the instrumentation is implemented -on top of this and uses a model roughly analogous to the compile-time hooks: - -```c - if (block_address > elf_text_start && block_address < elf_text_end) { - - cur_location = (block_address >> 4) ^ (block_address << 8); - shared_mem[cur_location ^ prev_location]++; - prev_location = cur_location >> 1; - - } -``` - -The shift-and-XOR-based scrambling in the second line is used to mask the -effects of instruction alignment. - -The start-up of binary translators such as QEMU, DynamoRIO, and PIN is fairly -slow; to counter this, the QEMU mode leverages a fork server similar to that -used for compiler-instrumented code, effectively spawning copies of an -already-initialized process paused at `_start`. - -First-time translation of a new basic block also incurs substantial latency. To -eliminate this problem, the AFL fork server is extended by providing a channel -between the running emulator and the parent process. The channel is used -to notify the parent about the addresses of any newly-encountered blocks and to -add them to the translation cache that will be replicated for future child -processes. - -As a result of these two optimizations, the overhead of the QEMU mode is -roughly 2-5x, compared to 100x+ for PIN. - -## 13. The `afl-analyze` tool - -The file format analyzer is a simple extension of the minimization algorithm -discussed earlier on; instead of attempting to remove no-op blocks, the tool -performs a series of walking byte flips and then annotates runs of bytes -in the input file. - -It uses the following classification scheme: - - - "No-op blocks" - segments where bit flips cause no apparent changes to - control flow. Common examples may be comment sections, pixel data within - a bitmap file, etc. - - "Superficial content" - segments where some, but not all, bitflips - produce some control flow changes. Examples may include strings in rich - documents (e.g., XML, RTF). - - "Critical stream" - a sequence of bytes where all bit flips alter control - flow in different but correlated ways. This may be compressed data, - non-atomically compared keywords or magic values, etc. - - "Suspected length field" - small, atomic integer that, when touched in - any way, causes a consistent change to program control flow, suggestive - of a failed length check. - - "Suspected cksum or magic int" - an integer that behaves similarly to a - length field, but has a numerical value that makes the length explanation - unlikely. This is suggestive of a checksum or other "magic" integer. - - "Suspected checksummed block" - a long block of data where any change - always triggers the same new execution path. Likely caused by failing - a checksum or a similar integrity check before any subsequent parsing - takes place. - - "Magic value section" - a generic token where changes cause the type - of binary behavior outlined earlier, but that doesn't meet any of the - other criteria. May be an atomically compared keyword or so. diff --git a/docs/third_party_tools.md b/docs/third_party_tools.md new file mode 100644 index 00000000..92229e84 --- /dev/null +++ b/docs/third_party_tools.md @@ -0,0 +1,57 @@ +# Tools that help fuzzing with AFL++ + +Speeding up fuzzing: +* [libfiowrapper](https://github.com/marekzmyslowski/libfiowrapper) - if the + function you want to fuzz requires loading a file, this allows using the + shared memory test case feature :-) - recommended. + +Minimization of test cases: +* [afl-pytmin](https://github.com/ilsani/afl-pytmin) - a wrapper for afl-tmin + that tries to speed up the process of minimization of a single test case by + using many CPU cores. +* [afl-ddmin-mod](https://github.com/MarkusTeufelberger/afl-ddmin-mod) - a + variation of afl-tmin based on the ddmin algorithm. +* [halfempty](https://github.com/googleprojectzero/halfempty) - is a fast + utility for minimizing test cases by Tavis Ormandy based on parallelization. + +Distributed execution: +* [disfuzz-afl](https://github.com/MartijnB/disfuzz-afl) - distributed fuzzing + for AFL. +* [AFLDFF](https://github.com/quantumvm/AFLDFF) - AFL distributed fuzzing + framework. +* [afl-launch](https://github.com/bnagy/afl-launch) - a tool for the execution + of many AFL instances. +* [afl-mothership](https://github.com/afl-mothership/afl-mothership) - + management and execution of many synchronized AFL fuzzers on AWS cloud. +* [afl-in-the-cloud](https://github.com/abhisek/afl-in-the-cloud) - another + script for running AFL in AWS. + +Deployment, management, monitoring, reporting +* [afl-utils](https://gitlab.com/rc0r/afl-utils) - a set of utilities for + automatic processing/analysis of crashes and reducing the number of test + cases. +* [afl-other-arch](https://github.com/shellphish/afl-other-arch) - is a set of + patches and scripts for easily adding support for various non-x86 + architectures for AFL. +* [afl-trivia](https://github.com/bnagy/afl-trivia) - a few small scripts to + simplify the management of AFL. +* [afl-monitor](https://github.com/reflare/afl-monitor) - a script for + monitoring AFL. +* [afl-manager](https://github.com/zx1340/afl-manager) - a web server on Python + for managing multi-afl. +* [afl-remote](https://github.com/block8437/afl-remote) - a web server for the + remote management of AFL instances. +* [afl-extras](https://github.com/fekir/afl-extras) - shell scripts to + parallelize afl-tmin, startup, and data collection. + +Crash processing +* [afl-crash-analyzer](https://github.com/floyd-fuh/afl-crash-analyzer) - + another crash analyzer for AFL. +* [fuzzer-utils](https://github.com/ThePatrickStar/fuzzer-utils) - a set of + scripts for the analysis of results. +* [atriage](https://github.com/Ayrx/atriage) - a simple triage tool. +* [afl-kit](https://github.com/kcwu/afl-kit) - afl-cmin on Python. +* [AFLize](https://github.com/d33tah/aflize) - a tool that automatically + generates builds of debian packages suitable for AFL. +* [afl-fid](https://github.com/FoRTE-Research/afl-fid) - a set of tools for + working with input data. \ No newline at end of file diff --git a/docs/tutorials.md b/docs/tutorials.md new file mode 100644 index 00000000..ed8a7eec --- /dev/null +++ b/docs/tutorials.md @@ -0,0 +1,30 @@ +# Tutorials + +Here are some good write-ups to show how to effectively use AFL++: + +* [https://aflplus.plus/docs/tutorials/libxml2_tutorial/](https://aflplus.plus/docs/tutorials/libxml2_tutorial/) +* [https://bananamafia.dev/post/gb-fuzz/](https://bananamafia.dev/post/gb-fuzz/) +* [https://securitylab.github.com/research/fuzzing-challenges-solutions-1](https://securitylab.github.com/research/fuzzing-challenges-solutions-1) +* [https://securitylab.github.com/research/fuzzing-software-2](https://securitylab.github.com/research/fuzzing-software-2) +* [https://securitylab.github.com/research/fuzzing-sockets-FTP](https://securitylab.github.com/research/fuzzing-sockets-FTP) +* [https://securitylab.github.com/research/fuzzing-sockets-FreeRDP](https://securitylab.github.com/research/fuzzing-sockets-FreeRDP) +* [https://securitylab.github.com/research/fuzzing-apache-1](https://securitylab.github.com/research/fuzzing-apache-1) + +If you do not want to follow a tutorial but rather try an exercise type of +training, then we can highly recommend the following: + +* [https://github.com/antonio-morales/Fuzzing101](https://github.com/antonio-morales/Fuzzing101) + +If you are interested in fuzzing structured data (where you define what the +structure is), these links have you covered: + +* Superion for AFL++: + [https://github.com/adrian-rt/superion-mutator](https://github.com/adrian-rt/superion-mutator) +* libprotobuf for AFL++: + [https://github.com/P1umer/AFLplusplus-protobuf-mutator](https://github.com/P1umer/AFLplusplus-protobuf-mutator) +* libprotobuf raw: + [https://github.com/bruce30262/libprotobuf-mutator_fuzzing_learning/tree/master/4_libprotobuf_aflpp_custom_mutator](https://github.com/bruce30262/libprotobuf-mutator_fuzzing_learning/tree/master/4_libprotobuf_aflpp_custom_mutator) +* libprotobuf for old AFL++ API: + [https://github.com/thebabush/afl-libprotobuf-mutator](https://github.com/thebabush/afl-libprotobuf-mutator) + +If you find other good ones, please send them to us :-) \ No newline at end of file |