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diff --git a/docs/README.md b/docs/README.md index cfa1cfc6..32d46ee8 100644..120000 --- a/docs/README.md +++ b/docs/README.md @@ -1,682 +1 @@ -# american fuzzy lop plus plus (afl++) - -  - - Release Version: 2.60c - - Github Version: 2.60d - - includes all necessary/interesting changes from Google's afl 2.56b - - - Originally developed by Michal "lcamtuf" Zalewski. - - Repository: [https://github.com/AFLplusplus/AFLplusplus](https://github.com/AFLplusplus/AFLplusplus) - - afl++ is maintained by Marc "van Hauser" Heuse <mh@mh-sec.de>, - Heiko "hexcoder-" Eißfeldt <heiko.eissfeldt@hexco.de>, Andrea Fioraldi <andreafioraldi@gmail.com> and Dominik Maier <mail@dmnk.co>. - - Note that although afl now has a Google afl repository [https://github.com/Google/afl](https://github.com/Google/afl), - it is unlikely to receive any noteable enhancements: [https://twitter.com/Dor3s/status/1154737061787660288](https://twitter.com/Dor3s/status/1154737061787660288) - - -## The enhancements compared to the original stock afl - - Many improvements were made over the official afl release - which did not - get any feature improvements since November 2017. - - Among other changes afl++ has a more performant llvm_mode, supports - llvm up to version 11, QEMU 3.1, more speed and crashfixes for QEMU, - better *BSD and Android support and much, much more. - - Additionally the following features and patches have been integrated: - - * AFLfast's power schedules by Marcel Böhme: [https://github.com/mboehme/aflfast](https://github.com/mboehme/aflfast) - - * The new excellent MOpt mutator: [https://github.com/puppet-meteor/MOpt-AFL](https://github.com/puppet-meteor/MOpt-AFL) - - * InsTrim, a very effective CFG llvm_mode instrumentation implementation for large targets: [https://github.com/csienslab/instrim](https://github.com/csienslab/instrim) - - * C. Holler's afl-fuzz Python mutator module and llvm_mode whitelist support: [https://github.com/choller/afl](https://github.com/choller/afl) - - * Custom mutator by a library (instead of Python) by kyakdan - - * unicorn_mode which allows fuzzing of binaries from completely different platforms (integration provided by domenukk) - - * laf-intel or CompCov support for llvm_mode, qemu_mode and unicorn_mode - - * NeverZero patch for afl-gcc, llvm_mode, qemu_mode and unicorn_mode which prevents a wrapping map value to zero, increases coverage - - * Persistent mode and deferred forkserver for qemu_mode - - * Win32 PE binary-only fuzzing with QEMU and Wine - - * Radamsa mutator (enable with `-R` to add or `-RR` to run it exclusivly). - - * qbdi_mode: fuzz android native libraries via QBDI framework - - - A more thorough list is available in the PATCHES file. - - | Feature/Instrumentation | afl-gcc | llvm_mode | gcc_plugin | qemu_mode | unicorn_mode | - | ----------------------- |:-------:|:---------:|:----------:|:---------:|:------------:| - | laf-intel / CompCov | | x | | x86/arm | x86/arm | - | NeverZero | x | x(1) | (2) | x | x | - | Persistent mode | | x | x | x86 | x | - | Whitelist | | x | x | | | - | InsTrim | | x | | | | - - neverZero: - - (1) only in LLVM >= 9.0 due to a bug in llvm in previous versions - - (2) gcc creates non-performant code, hence it is disabled in gcc_plugin - - So all in all this is the best-of afl that is currently out there :-) - - For new versions and additional information, check out: - [https://github.com/AFLplusplus/AFLplusplus](https://github.com/AFLplusplus/AFLplusplus) - - To compare notes with other users or get notified about major new features, - send a mail to <afl-users+subscribe@googlegroups.com>. - - See [docs/QuickStartGuide.md](docs/QuickStartGuide.md) if you don't have time to - read this file. - - -## 0) Building and installing afl++ - -afl++ has many build options. -The easiest is to build and install everything: - -```shell -$ make distrib -$ sudo make install -``` - -Note that "make distrib" also builds llvm_mode, qemu_mode, unicorn_mode and -more. If you just want plain afl then do "make all", however compiling and -using at least llvm_mode is highly recommended for much better results - -hence in this case - -```shell -$ make source-only -``` -is what you should choose. - -These build options exist: - -* all: just the main afl++ binaries -* binary-only: everything for binary-only fuzzing: qemu_mode, unicorn_mode, libdislocator, libtokencap, radamsa -* source-only: everything for source code fuzzing: llvm_mode, libdislocator, libtokencap, radamsa -* distrib: everything (for both binary-only and source code fuzzing) -* install: installs everything you have compiled with the build options above -* clean: cleans everything. for qemu_mode and unicorn_mode it means it deletes all downloads as well -* 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 -* 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 all STATIC=1 -``` - -Note that afl++ is faster and better the newer the compilers used are. -Hence gcc-9 and especially llvm-9 should be the compilers of choice. -If your distribution does not have them, you can use the Dockerfile: - -```shell -$ docker build -t aflplusplus -``` - - -## 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 3.8.0 to 11. - -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: - -```shell -$ 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.md](llvm_mode/README.md). -Clang/LLVM has a much better performance and works with LLVM version 3.8.0 to 11. - -Using the LAF Intel performance enhancements are also recommended, see -[llvm_mode/README.laf-intel.md](llvm_mode/README.laf-intel.md) - -Using partial instrumentation is also recommended, see -[llvm_mode/README.whitelist.md](llvm_mode/README.whitelist.md) - -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: - -```shell -$ 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.md](libdislocator/README.md)) can help uncover heap corruption issues, too. - -PS. ASAN users are advised to review [docs/notes_for_asan.md](docs/notes_for_asan.md) -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: - -```shell -$ cd qemu_mode -$ ./build_qemu_support.sh -``` - -For additional instructions and caveats, see [qemu_mode/README.md](qemu_mode/README.md). - -The mode is approximately 2-5x slower than compile-time instrumentation, is -less conducive 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. - -A more comprehensive description of these and other options can be found in -[docs/binaryonly_fuzzing.md](docs/binaryonly_fuzzing.md) - - -## 5) Power schedules - -The power schedules were copied from Marcel Böhme's excellent AFLfast -implementation and expand on the ability to discover new paths and -therefore may increase the code 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.md](docs/perf_tips.md). - - - 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: - -```shell -$ ./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: - -```shell -$ ./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.md](docs/perf_tips.md). - -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 [docs/status_screen.md](docs/status_screen.md) 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: - -```shell -$ LIMIT_MB=50 -$ ( ulimit -Sv $[LIMIT_MB << 10]; /path/to/tested_binary ... ) -``` - -Change LIMIT_MB to match the -m parameter passed to afl-fuzz. On OpenBSD, -also change -Sv to -Sd. - -Any existing output directory can be also used to resume aborted jobs; try: - -```shell -$ ./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/](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 [docs/parallel_fuzzing.md](docs/parallel_fuzzing.md). - -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 [docs/parallel_fuzzing.md](docs/parallel_fuzzing.md) 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](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.md](dictionaries/README.md); -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](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.md](libtokencap/README.tokencap.md). - - -## 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: - -```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 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 [docs/technical_details.md](docs/technical_details.md). - - -## 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: - -```shell - $ 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 - examples/libpng_no_checksum/ for inspiration); if this is not possible, - you can also write a postprocessor, as explained in - examples/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 [docs/notes_for_asan.md](docs/notes_for_asan.md) - 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](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) - - - 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](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/](http://lcamtuf.coredump.cx/prep/). - -Beyond this, see INSTALL for platform-specific tips. - - -## 15) Special thanks - -Many of the improvements to the original afl and afl++ 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 Neuschaefer 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 Boehme - Van-Thuan Pham Abhik Roychoudhury - Joshua J. Drake Toby Hutton - Rene Freingruber Sergey Davidoff - Sami Liedes Craig Young - Andrzej Jackowski Daniel Hodson - Nathan Voss Dominik Maier - Andrea Biondo Vincent Le Garrec - Khaled Yakdan Kuang-che Wu -``` - -Thank you! - - -## 16) Contact - -Questions? Concerns? Bug reports? The contributors can be reached via -[https://github.com/AFLplusplus/AFLplusplus](https://github.com/AFLplusplus/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](https://groups.google.com/group/afl-users) +../README.md \ No newline at end of file |