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189 lines
7.7 KiB
189 lines
7.7 KiB
============================================
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Fast LLVM-based instrumentation for afl-fuzz
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============================================
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(See ../docs/README for the general instruction manual.)
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1) Introduction
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---------------
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The code in this directory allows you to instrument programs for AFL using
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true compiler-level instrumentation, instead of the more crude
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assembly-level rewriting approach taken by afl-gcc and afl-clang. This has
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several interesting properties:
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- The compiler can make many optimizations that are hard to pull off when
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manually inserting assembly. As a result, some slow, CPU-bound programs will
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run up to around 2x faster.
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The gains are less pronounced for fast binaries, where the speed is limited
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chiefly by the cost of creating new processes. In such cases, the gain will
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probably stay within 10%.
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- The instrumentation is CPU-independent. At least in principle, you should
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be able to rely on it to fuzz programs on non-x86 architectures (after
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building afl-fuzz with AFL_NO_X86=1).
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- The instrumentation can cope a bit better with multi-threaded targets.
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- Because the feature relies on the internals of LLVM, it is clang-specific
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and will *not* work with GCC.
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Once this implementation is shown to be sufficiently robust and portable, it
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will probably replace afl-clang. For now, it can be built separately and
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co-exists with the original code.
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The idea and much of the implementation comes from Laszlo Szekeres.
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2) How to use
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-------------
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In order to leverage this mechanism, you need to have clang installed on your
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system. You should also make sure that the llvm-config tool is in your path
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(or pointed to via LLVM_CONFIG in the environment).
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Unfortunately, some systems that do have clang come without llvm-config or the
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LLVM development headers; one example of this is FreeBSD. FreeBSD users will
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also run into problems with clang being built statically and not being able to
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load modules (you'll see "Service unavailable" when loading afl-llvm-pass.so).
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To solve all your problems, you can grab pre-built binaries for your OS from:
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http://llvm.org/releases/download.html
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...and then put the bin/ directory from the tarball at the beginning of your
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$PATH when compiling the feature and building packages later on. You don't need
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to be root for that.
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To build the instrumentation itself, type 'make'. This will generate binaries
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called afl-clang-fast and afl-clang-fast++ in the parent directory. Once this
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is done, you can instrument third-party code in a way similar to the standard
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operating mode of AFL, e.g.:
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CC=/path/to/afl/afl-clang-fast ./configure [...options...]
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make
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Be sure to also include CXX set to afl-clang-fast++ for C++ code.
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The tool honors roughly the same environmental variables as afl-gcc (see
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../docs/env_variables.txt). This includes AFL_INST_RATIO, AFL_USE_ASAN,
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AFL_HARDEN, and AFL_DONT_OPTIMIZE.
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Note: if you want the LLVM helper to be installed on your system for all
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users, you need to build it before issuing 'make install' in the parent
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directory.
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3) Gotchas, feedback, bugs
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--------------------------
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This is an early-stage mechanism, so field reports are welcome. You can send bug
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reports to <afl-users@googlegroups.com>.
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4) Bonus feature #1: deferred instrumentation
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---------------------------------------------
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AFL tries to optimize performance by executing the targeted binary just once,
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stopping it just before main(), and then cloning this "master" process to get
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a steady supply of targets to fuzz.
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Although this approach eliminates much of the OS-, linker- and libc-level
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costs of executing the program, it does not always help with binaries that
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perform other time-consuming initialization steps - say, parsing a large config
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file before getting to the fuzzed data.
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In such cases, it's beneficial to initialize the forkserver a bit later, once
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most of the initialization work is already done, but before the binary attempts
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to read the fuzzed input and parse it; in some cases, this can offer a 10x+
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performance gain. You can implement delayed initialization in LLVM mode in a
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fairly simple way.
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First, find a suitable location in the code where the delayed cloning can
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take place. This needs to be done with *extreme* care to avoid breaking the
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binary. In particular, the program will probably malfunction if you select
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a location after:
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- The creation of any vital threads or child processes - since the forkserver
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can't clone them easily.
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- The initialization of timers via setitimer() or equivalent calls.
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- The creation of temporary files, network sockets, offset-sensitive file
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descriptors, and similar shared-state resources - but only provided that
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their state meaningfully influences the behavior of the program later on.
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- Any access to the fuzzed input, including reading the metadata about its
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size.
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With the location selected, add this code in the appropriate spot:
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#ifdef __AFL_HAVE_MANUAL_CONTROL
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__AFL_INIT();
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#endif
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You don't need the #ifdef guards, but including them ensures that the program
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will keep working normally when compiled with a tool other than afl-clang-fast.
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Finally, recompile the program with afl-clang-fast (afl-gcc or afl-clang will
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*not* generate a deferred-initialization binary) - and you should be all set!
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5) Bonus feature #2: persistent mode
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------------------------------------
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Some libraries provide APIs that are stateless, or whose state can be reset in
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between processing different input files. When such a reset is performed, a
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single long-lived process can be reused to try out multiple test cases,
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eliminating the need for repeated fork() calls and the associated OS overhead.
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The basic structure of the program that does this would be:
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while (__AFL_LOOP(1000)) {
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/* Read input data. */
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/* Call library code to be fuzzed. */
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/* Reset state. */
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}
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/* Exit normally */
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The numerical value specified within the loop controls the maximum number
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of iterations before AFL will restart the process from scratch. This minimizes
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the impact of memory leaks and similar glitches; 1000 is a good starting point,
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and going much higher increases the likelihood of hiccups without giving you
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any real performance benefits.
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A more detailed template is shown in ../experimental/persistent_demo/.
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Similarly to the previous mode, the feature works only with afl-clang-fast;
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#ifdef guards can be used to suppress it when using other compilers.
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Note that as with the previous mode, the feature is easy to misuse; if you
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do not fully reset the critical state, you may end up with false positives or
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waste a whole lot of CPU power doing nothing useful at all. Be particularly
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wary of memory leaks and of the state of file descriptors.
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PS. Because there are task switches still involved, the mode isn't as fast as
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"pure" in-process fuzzing offered, say, by LLVM's LibFuzzer; but it is a lot
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faster than the normal fork() model, and compared to in-process fuzzing,
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should be a lot more robust.
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6) Bonus feature #3: new 'trace-pc-guard' mode
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----------------------------------------------
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Recent versions of LLVM are shipping with a built-in execution tracing feature
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that provides AFL with the necessary tracing data without the need to
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post-process the assembly or install any compiler plugins. See:
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http://clang.llvm.org/docs/SanitizerCoverage.html#tracing-pcs-with-guards
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If you have a sufficiently recent compiler and want to give it a try, build
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afl-clang-fast this way:
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AFL_TRACE_PC=1 make clean all
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Note that this mode is currently about 20% slower than "vanilla" afl-clang-fast,
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and about 5-10% slower than afl-clang. This is likely because the
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instrumentation is not inlined, and instead involves a function call. On systems
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that support it, compiling your target with -flto should help.
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