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diff --git a/docs/README b/docs/README deleted file mode 100644 index c2c93f38..00000000 --- a/docs/README +++ /dev/null @@ -1,592 +0,0 @@ -============================ -american fuzzy lop plus plus -============================ - - Originally written by Michal Zalewski <lcamtuf@google.com> - - Repository: https://github.com/vanhauser-thc/AFLplusplus - - afl++ is maintained by Marc Heuse <mh@mh-sec.de>, Heiko Eissfeldt - <heiko.eissfeldt@hexco.de> and Andrea Fioraldi <andreafioraldi@gmail.com> as - there have been no updates to afl since November 2017. - - - Many improvements were made, e.g. more performant llvm_mode, supporting - llvm up to version 8, Qemu 3.1, more speed and crashfixes for Qemu, - laf-intel feature for Qemu (with libcompcov) etc. - - Additionally AFLfast's power schedules by Marcel Boehme from - https://github.com/mboehme/aflfast have been incorporated. - - C. Hollers afl-fuzz Python mutator module and llvm_mode whitelist support - was added too (https://github.com/choller/afl) - - New is the excellent MOpt mutator from - https://github.com/puppet-meteor/MOpt-AFL - - Also newly integrated is instrim, a very effective CFG llvm_mode - instrumentation implementation from https://github.com/csienslab/instrim - - And finally the newest addition is the unicorn_mode which allows fuzzing - of binaries from completely different platforms - provided by domenukk! - The unicorn afl mode is not the stock version but like afl++ contains - various patches from forks that make it better :) - - A more thorough list is available in the PATCHES file. - - So all in all this is the best-of AFL that is currently out there :-) - - - Copyright 2013, 2014, 2015, 2016 Google Inc. All rights reserved. - Released under terms and conditions of Apache License, Version 2.0. - - For new versions and additional information, check out: - https://github.com/vanhauser-thc/AFLplusplus - - To compare notes with other users or get notified about major new features, - send a mail to <afl-users+subscribe@googlegroups.com>. - - ** See QuickStartGuide.txt if you don't have time to read this file. ** - - -1) Challenges of guided fuzzing -------------------------------- - -Fuzzing is one of the most powerful and proven strategies for identifying -security issues in real-world software; it is responsible for the vast -majority of remote code execution and privilege escalation bugs found to date -in security-critical software. - -Unfortunately, fuzzing is also relatively shallow; blind, random mutations -make it very unlikely to reach certain code paths in the tested code, leaving -some vulnerabilities firmly outside the reach of this technique. - -There have been numerous attempts to solve this problem. One of the early -approaches - pioneered by Tavis Ormandy - is corpus distillation. The method -relies on coverage signals to select a subset of interesting seeds from a -massive, high-quality corpus of candidate files, and then fuzz them by -traditional means. The approach works exceptionally well, but requires such -a corpus to be readily available. In addition, block coverage measurements -provide only a very simplistic understanding of program state, and are less -useful for guiding the fuzzing effort in the long haul. - -Other, more sophisticated research has focused on techniques such as program -flow analysis ("concolic execution"), symbolic execution, or static analysis. -All these methods are extremely promising in experimental settings, but tend -to suffer from reliability and performance problems in practical uses - and -currently do not offer a viable alternative to "dumb" fuzzing techniques. - - -2) The afl-fuzz approach ------------------------- - -American Fuzzy Lop 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 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. - - -3) Instrumenting programs for use with AFL ------------------------------------------- - -PLEASE NOTE: llvm_mode compilation with afl-clang-fast/afl-clang-fast++ -instead of afl-gcc/afl-g++ is much faster and has a few cool features. -See llvm_mode/ - however few code does not compile with llvm. -We support llvm versions 4.0 to 8. - -When source code is available, instrumentation can be injected by a companion -tool that works as a drop-in replacement for gcc or clang in any standard build -process for third-party code. - -The instrumentation has a fairly modest performance impact; in conjunction with -other optimizations implemented by afl-fuzz, most programs can be fuzzed as fast -or even faster than possible with traditional tools. - -The correct way to recompile the target program may vary depending on the -specifics of the build process, but a nearly-universal approach would be: - -$ CC=/path/to/afl/afl-gcc ./configure -$ make clean all - -For C++ programs, you'd would also want to set CXX=/path/to/afl/afl-g++. - -The clang wrappers (afl-clang and afl-clang++) can be used in the same way; -clang users may also opt to leverage a higher-performance instrumentation mode, -as described in llvm_mode/README.llvm. -Clang/LLVM has a much better performance and works from LLVM version 4.0 to 8. -Using the LAF Intel performance enhancements are also recommended, see -llvm_mode/README.laf-intel -Using partial instrumentation is also recommended, see -llvm_mode/README.whitelist - -When testing libraries, you need to find or write a simple program that reads -data from stdin or from a file and passes it to the tested library. In such a -case, it is essential to link this executable against a static version of the -instrumented library, or to make sure that the correct .so file is loaded at -runtime (usually by setting LD_LIBRARY_PATH). The simplest option is a static -build, usually possible via: - -$ CC=/path/to/afl/afl-gcc ./configure --disable-shared - -Setting AFL_HARDEN=1 when calling 'make' will cause the CC wrapper to -automatically enable code hardening options that make it easier to detect -simple memory bugs. Libdislocator, a helper library included with AFL (see -libdislocator/README.dislocator) can help uncover heap corruption issues, too. - -PS. ASAN users are advised to docs/review notes_for_asan.txt file for -important caveats. - - -4) Instrumenting binary-only apps ---------------------------------- - -When source code is *NOT* available, the fuzzer offers experimental support for -fast, on-the-fly instrumentation of black-box binaries. 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: - -$ cd qemu_mode -$ ./build_qemu_support.sh - -For additional instructions and caveats, see qemu_mode/README.qemu. - -The mode is approximately 2-5x slower than compile-time instrumentation, is -less conductive to parallelization, and may have some other quirks. - -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. - - -5) Power schedules ------------------- - -The power schedules were copied from Marcel Böhme's excellent AFLfast -implementation and expands on the ability to discover new paths and -therefore the coverage. - -The available schedules are: - - - explore (default) - - fast - - coe - - quad - - lin - - exploit - -In parallel mode (-M/-S, several instances with shared queue), we suggest to -run the master using the exploit schedule (-p exploit) and the slaves with a -combination of cut-off-exponential (-p coe), exponential (-p fast; default), -and explore (-p explore) schedules. - -In single mode, using -p fast is usually more beneficial than the default -explore mode. -(We don't want to change the default behaviour of afl, so "fast" has not been -made the default mode). - -More details can be found in the paper published at the 23rd ACM Conference on -Computer and Communications Security (CCS'16): - - https://www.sigsac.org/ccs/CCS2016/accepted-papers/ - -6) Choosing initial test cases ------------------------------- - -To operate correctly, the fuzzer requires one or more starting file that -contains a good example of the input data normally expected by the targeted -application. There are two basic rules: - - - Keep the files small. Under 1 kB is ideal, although not strictly necessary. - For a discussion of why size matters, see perf_tips.txt. - - - Use multiple test cases only if they are functionally different from - each other. There is no point in using fifty different vacation photos - to fuzz an image library. - -You can find many good examples of starting files in the testcases/ subdirectory -that comes with this tool. - -PS. If a large corpus of data is available for screening, you may want to use -the afl-cmin utility to identify a subset of functionally distinct files that -exercise different code paths in the target binary. - - -7) Fuzzing binaries -------------------- - -The fuzzing process itself is carried out by the afl-fuzz utility. This program -requires a read-only directory with initial test cases, a separate place to -store its findings, plus a path to the binary to test. - -For target binaries that accept input directly from stdin, the usual syntax is: - -$ ./afl-fuzz -i testcase_dir -o findings_dir /path/to/program [...params...] - -For programs that take input from a file, use '@@' to mark the location in -the target's command line where the input file name should be placed. The -fuzzer will substitute this for you: - -$ ./afl-fuzz -i testcase_dir -o findings_dir /path/to/program @@ - -You can also use the -f option to have the mutated data written to a specific -file. This is useful if the program expects a particular file extension or so. - -Non-instrumented binaries can be fuzzed in the QEMU mode (add -Q in the command -line) or in a traditional, blind-fuzzer mode (specify -n). - -You can use -t and -m to override the default timeout and memory limit for the -executed process; rare examples of targets that may need these settings touched -include compilers and video decoders. - -Tips for optimizing fuzzing performance are discussed in perf_tips.txt. - -Note that afl-fuzz starts by performing an array of deterministic fuzzing -steps, which can take several days, but tend to produce neat test cases. If you -want quick & dirty results right away - akin to zzuf and other traditional -fuzzers - add the -d option to the command line. - - -8) Interpreting output ----------------------- - -See the status_screen.txt file 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 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 - mentioned in section 2. - - 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 parent, non-faulting -queue entries. This should help with debugging. - -When you can't reproduce a crash found by afl-fuzz, the most likely cause is -that you are not setting the same memory limit as used by the tool. Try: - -$ LIMIT_MB=50 -$ ( ulimit -Sv $[LIMIT_MB << 10]; /path/to/tested_binary ... ) - -Change LIMIT_MB to match the -m parameter passed to afl-fuzz. On OpenBSD, -also change -Sv to -Sd. - -Any existing output directory can be also used to resume aborted jobs; try: - -$ ./afl-fuzz -i- -o existing_output_dir [...etc...] - -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 http://lcamtuf.coredump.cx/afl/plot/. - - -9) Parallelized fuzzing ------------------------ - -Every instance of afl-fuzz takes up roughly one core. This means that on -multi-core systems, parallelization is necessary to fully utilize the hardware. -For tips on how to fuzz a common target on multiple cores or multiple networked -machines, please refer to parallel_fuzzing.txt. - -The parallel fuzzing mode also offers a simple way for interfacing AFL to other -fuzzers, to symbolic or concolic execution engines, and so forth; again, see the -last section of parallel_fuzzing.txt for tips. - - -10) Fuzzer dictionaries ----------------------- - -By default, afl-fuzz mutation engine is optimized for compact data formats - -say, images, multimedia, compressed data, regular expression syntax, or shell -scripts. It is somewhat less suited for languages with particularly verbose and -redundant verbiage - notably including HTML, SQL, or JavaScript. - -To avoid the hassle of building syntax-aware tools, afl-fuzz provides a way to -seed the fuzzing process with an optional dictionary of language keywords, -magic headers, or other special tokens associated with the targeted data type -- and use that to reconstruct the underlying grammar on the go: - - http://lcamtuf.blogspot.com/2015/01/afl-fuzz-making-up-grammar-with.html - -To use this feature, you first need to create a dictionary in one of the two -formats discussed in dictionaries/README.dictionaries; and then point the fuzzer -to it via the -x option in the command line. - -(Several common dictionaries are already provided in that subdirectory, too.) - -There is no way to provide more structured descriptions of the underlying -syntax, but the fuzzer will likely figure out some of this based on the -instrumentation feedback alone. This actually works in practice, say: - - http://lcamtuf.blogspot.com/2015/04/finding-bugs-in-sqlite-easy-way.html - -PS. Even when no explicit dictionary is given, afl-fuzz will try to extract -existing syntax tokens in the input corpus by watching the instrumentation -very closely during deterministic byte flips. This works for some types of -parsers and grammars, but isn't nearly as good as the -x mode. - -If a dictionary is really hard to come by, another option is to let AFL run -for a while, and then use the token capture library that comes as a companion -utility with AFL. For that, see libtokencap/README.tokencap. - - -11) Crash triage ----------------- - -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: - -$ ./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 recent addition to 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. More info about its operation can be found -near the end of technical_details.txt. - - -12) 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) or #ifdef __AFL_COMPILER (this one is just for AFL). - - -13) Common-sense risks ----------------------- - -Please keep in mind that, similarly to many other computationally-intensive -tasks, fuzzing may put 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: - - $ iostat -d 3 -x -k [...optional disk ID...] - - -14) 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 processed 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 - experimental/libpng_no_checksum/ for inspiration); if this is not possible, - you can also write a postprocessor, as explained in - experimental/post_library/ (with AFL_POST_LIBRARY) - - - There are some unfortunate trade-offs with ASAN and 64-bit binaries. This - isn't due to any specific fault of afl-fuzz; see notes_for_asan.txt for - tips. - - - 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 - - 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 - - - AFL doesn't output human-readable coverage data. If you want to monitor - coverage, use afl-cov from Michael Rash: https://github.com/mrash/afl-cov - - - Occasionally, sentient machines rise against their creators. If this - happens to you, please consult http://lcamtuf.coredump.cx/prep/. - -Beyond this, see INSTALL for platform-specific tips. - - -15) Special thanks ------------------- - -Many of the improvements to afl-fuzz wouldn't be possible without feedback, -bug reports, or patches from: - - Jann Horn Hanno Boeck - Felix Groebert Jakub Wilk - Richard W. M. Jones Alexander Cherepanov - Tom Ritter Hovik Manucharyan - Sebastian Roschke Eberhard Mattes - Padraig Brady Ben Laurie - @dronesec Luca Barbato - Tobias Ospelt Thomas Jarosch - Martin Carpenter Mudge Zatko - Joe Zbiciak Ryan Govostes - Michael Rash William Robinet - Jonathan Gray Filipe Cabecinhas - Nico Weber Jodie Cunningham - Andrew Griffiths Parker Thompson - Jonathan Neuschfer Tyler Nighswander - Ben Nagy Samir Aguiar - Aidan Thornton Aleksandar Nikolich - Sam Hakim Laszlo Szekeres - David A. Wheeler Turo Lamminen - Andreas Stieger Richard Godbee - Louis Dassy teor2345 - Alex Moneger Dmitry Vyukov - Keegan McAllister Kostya Serebryany - Richo Healey Martijn Bogaard - rc0r Jonathan Foote - Christian Holler Dominique Pelle - Jacek Wielemborek Leo Barnes - Jeremy Barnes Jeff Trull - Guillaume Endignoux ilovezfs - Daniel Godas-Lopez Franjo Ivancic - Austin Seipp Daniel Komaromy - Daniel Binderman Jonathan Metzman - Vegard Nossum Jan Kneschke - Kurt Roeckx Marcel Bohme - Van-Thuan Pham Abhik Roychoudhury - Joshua J. Drake Toby Hutton - Rene Freingruber Sergey Davidoff - Sami Liedes Craig Young - Andrzej Jackowski Daniel Hodson - -Thank you! - - -16) Contact ------------ - -Questions? Concerns? Bug reports? The contributors can be reached via -https://github.com/vanhauser-thc/AFLplusplus - -There is also a mailing list for the afl project; to join, send a mail to -<afl-users+subscribe@googlegroups.com>. Or, if you prefer to browse -archives first, try: - - https://groups.google.com/group/afl-users |