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diff --git a/docs/FAQ.md b/docs/FAQ.md index 0e816062..560f37bf 100644 --- a/docs/FAQ.md +++ b/docs/FAQ.md @@ -1,4 +1,7 @@ -# Frequently asked questions about AFL++ +# Frequently asked questions and troubleshooting + +If you find an interesting or important question missing, submit it via +[https://github.com/AFLplusplus/AFLplusplus/issues](https://github.com/AFLplusplus/AFLplusplus/issues). ## Contents @@ -11,30 +14,11 @@ * [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) -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. +AFL++ is a superior fork to Google's AFL - more speed, more and better mutations, more and better instrumentation, custom module support, etc. -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) +For more information about the history of AFL++, see [docs/history_afl++.md](docs/history_afl++.md). ## I got a weird compile error from clang @@ -58,51 +42,21 @@ 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? +See [docs/best_practices.md#improving-speed](docs/best_practices.md#improving-speed). -The short answer is - you cannot, at least not "out of the box". +## How can I improve the stability value? -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). +See [docs/best_practices.md#improving-stability](docs/best_practices.md#improving-stability). -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!). +## How do I fuzz a network service? -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/). +The short answer is - you cannot, at least not "out of the box". -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. +For more information, see [docs/best_practices.md#fuzzing-network-service](docs/best_practices.md#fuzzing-network-service). ## 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. +See [docs/best_practices.md#fuzzing-gui-program](docs/best_practices.md#fuzzing-gui-program). ## What is an "edge"? @@ -154,7 +108,7 @@ Stability is measured by how many percent of the edges in the target are 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 +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". @@ -165,79 +119,3 @@ 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) diff --git a/docs/best_practices.md b/docs/best_practices.md new file mode 100644 index 00000000..e08ae6ab --- /dev/null +++ b/docs/best_practices.md @@ -0,0 +1,103 @@ +# Best practices + +## Improvements + +### Improving speed <a name="#improving-speed"></a> + + 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). + +### Improving stability <a name="#improving-stability"></a> + +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+!): + [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. Recompile the target + + Recompile, fuzz it, be happy :) + + This link explains this process for [Fuzzbench](https://github.com/google/fuzzbench/issues/677). + +## Targets + +### Fuzzing a GUI program <a name="#fuzzing-gui-program"></a> + +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 <a name="#fuzzing-network-service"></a> + +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. \ No newline at end of file diff --git a/docs/history_afl++.md b/docs/history_afl++.md new file mode 100644 index 00000000..ff06a372 --- /dev/null +++ b/docs/history_afl++.md @@ -0,0 +1,12 @@ +# History of 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 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) \ No newline at end of file |