diff --git a/README1.md b/README1.md new file mode 100644 index 0000000..6e34d4e --- /dev/null +++ b/README1.md @@ -0,0 +1,493 @@ +# american fuzzy lop + +[![Build Status](https://travis-ci.org/google/AFL.svg?branch=master)](https://travis-ci.org/google/AFL) + +Originally developed by Michal Zalewski . + +See [QuickStartGuide.txt](docs/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 + +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.llvm. + +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.dislocator) can help uncover heap corruption issues, too. + +PS. ASAN users are advised to review [notes_for_asan.txt](docs/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: + +```shell +$ 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 conducive to parallelization, and may have some other quirks. + +## 5) 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](docs/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. + +## 6) 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.txt](docs/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. + +## 7) Interpreting output + +See the [status_screen.txt](docs/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: + +```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/). + +## 8) 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](docs/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](docs/parallel_fuzzing.txt) for tips. + +## 9) 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.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](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. + +## 10) 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 [technical_details.txt](docs/technical_details.txt). + +## 11) 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). + +## 12) 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...] +``` + +## 13) 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/. + + - 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](docs/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. + +## 14) 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! + +## 15) Contact + +Questions? Concerns? Bug reports? Please use GitHub. + +There is also a mailing list for the project; to join, send a mail to +. Or, if you prefer to browse +archives first, try: [https://groups.google.com/group/afl-users](https://groups.google.com/group/afl-users).