1 ========================================================
2 LibFuzzer -- a library for coverage-guided fuzz testing.
3 ========================================================
11 This library is intended primarily for in-process coverage-guided fuzz testing
12 (fuzzing) of other libraries. The typical workflow looks like this:
14 * Build the Fuzzer library as a static archive (or just a set of .o files).
15 Note that the Fuzzer contains the main() function.
16 Preferably do *not* use sanitizers while building the Fuzzer.
17 * Build the library you are going to test with -fsanitize-coverage=[234]
18 and one of the sanitizers. We recommend to build the library in several
19 different modes (e.g. asan, msan, lsan, ubsan, etc) and even using different
20 optimizations options (e.g. -O0, -O1, -O2) to diversify testing.
21 * Build a test driver using the same options as the library.
22 The test driver is a C/C++ file containing interesting calls to the library
23 inside a single function ``extern "C" void TestOneInput(const uint8_t *Data, size_t Size);``
24 * Link the Fuzzer, the library and the driver together into an executable
25 using the same sanitizer options as for the library.
26 * Collect the initial corpus of inputs for the
27 fuzzer (a directory with test inputs, one file per input).
28 The better your inputs are the faster you will find something interesting.
29 Also try to keep your inputs small, otherwise the Fuzzer will run too slow.
30 * Run the fuzzer with the test corpus. As new interesting test cases are
31 discovered they will be added to the corpus. If a bug is discovered by
32 the sanitizer (asan, etc) it will be reported as usual and the reproducer
33 will be written to disk.
34 Each Fuzzer process is single-threaded (unless the library starts its own
35 threads). You can run the Fuzzer on the same corpus in multiple processes.
36 in parallel. For run-time options run the Fuzzer binary with '-help=1'.
39 The Fuzzer is similar in concept to AFL_,
40 but uses in-process Fuzzing, which is more fragile, more restrictive, but
41 potentially much faster as it has no overhead for process start-up.
42 It uses LLVM's SanitizerCoverage_ instrumentation to get in-process
45 The code resides in the LLVM repository, requires the fresh Clang compiler to build
46 and is used to fuzz various parts of LLVM,
47 but the Fuzzer itself does not (and should not) depend on any
48 part of LLVM and can be used for other projects w/o requiring the rest of LLVM.
56 A simple function that does something interesting if it receives the input "HI!"::
58 cat << EOF >> test_fuzzer.cc
59 extern "C" void TestOneInput(const unsigned char *data, unsigned long size) {
60 if (size > 0 && data[0] == 'H')
61 if (size > 1 && data[1] == 'I')
62 if (size > 2 && data[2] == '!')
66 # Get lib/Fuzzer. Assuming that you already have fresh clang in PATH.
67 svn co http://llvm.org/svn/llvm-project/llvm/trunk/lib/Fuzzer
68 # Build lib/Fuzzer files.
69 clang -c -g -O2 -std=c++11 Fuzzer/*.cpp -IFuzzer
70 # Build test_fuzzer.cc with asan and link against lib/Fuzzer.
71 clang++ -fsanitize=address -fsanitize-coverage=3 test_fuzzer.cc Fuzzer*.o
72 # Run the fuzzer with no corpus.
75 You should get ``Illegal instruction (core dumped)`` pretty quickly.
80 Here we show how to use lib/Fuzzer on something real, yet simple: pcre2_::
82 COV_FLAGS=" -fsanitize-coverage=4 -mllvm -sanitizer-coverage-8bit-counters=1"
84 svn co svn://vcs.exim.org/pcre2/code/trunk pcre
85 # Get lib/Fuzzer. Assuming that you already have fresh clang in PATH.
86 svn co http://llvm.org/svn/llvm-project/llvm/trunk/lib/Fuzzer
87 # Build PCRE2 with AddressSanitizer and coverage.
88 (cd pcre; ./autogen.sh; CC="clang -fsanitize=address $COV_FLAGS" ./configure --prefix=`pwd`/../inst && make -j && make install)
89 # Build lib/Fuzzer files.
90 clang -c -g -O2 -std=c++11 Fuzzer/*.cpp -IFuzzer
91 # Build the the actual function that does something interesting with PCRE2.
92 cat << EOF > pcre_fuzzer.cc
94 #include "pcre2posix.h"
95 extern "C" void TestOneInput(const unsigned char *data, size_t size) {
97 char *str = new char[size+1];
98 memcpy(str, data, size);
101 if (0 == regcomp(&preg, str, 0)) {
102 regexec(&preg, str, 0, 0, 0);
108 clang++ -g -fsanitize=address $COV_FLAGS -c -std=c++11 -I inst/include/ pcre_fuzzer.cc
110 clang++ -g -fsanitize=address -Wl,--whole-archive inst/lib/*.a -Wl,-no-whole-archive Fuzzer*.o pcre_fuzzer.o -o pcre_fuzzer
112 This will give you a binary of the fuzzer, called ``pcre_fuzzer``.
113 Now, create a directory that will hold the test corpus::
117 For simple input languages like regular expressions this is all you need.
118 For more complicated inputs populate the directory with some input samples.
119 Now run the fuzzer with the corpus dir as the only parameter::
121 ./pcre_fuzzer ./CORPUS
123 You will see output like this::
126 #0 READ cov 0 bits 0 units 1 exec/s 0
127 #1 pulse cov 3 bits 0 units 1 exec/s 0
128 #1 INITED cov 3 bits 0 units 1 exec/s 0
129 #2 pulse cov 208 bits 0 units 1 exec/s 0
130 #2 NEW cov 208 bits 0 units 2 exec/s 0 L: 64
131 #3 NEW cov 217 bits 0 units 3 exec/s 0 L: 63
132 #4 pulse cov 217 bits 0 units 3 exec/s 0
134 * The ``Seed:`` line shows you the current random seed (you can change it with ``-seed=N`` flag).
135 * The ``READ`` line shows you how many input files were read (since you passed an empty dir there were inputs, but one dummy input was synthesised).
136 * The ``INITED`` line shows you that how many inputs will be fuzzed.
137 * The ``NEW`` lines appear with the fuzzer finds a new interesting input, which is saved to the CORPUS dir. If multiple corpus dirs are given, the first one is used.
138 * The ``pulse`` lines appear periodically to show the current status.
140 Now, interrupt the fuzzer and run it again the same way. You will see::
143 #0 READ cov 0 bits 0 units 564 exec/s 0
144 #1 pulse cov 502 bits 0 units 564 exec/s 0
146 #512 pulse cov 2933 bits 0 units 564 exec/s 512
147 #564 INITED cov 2991 bits 0 units 344 exec/s 564
148 #1024 pulse cov 2991 bits 0 units 344 exec/s 1024
149 #1455 NEW cov 2995 bits 0 units 345 exec/s 1455 L: 49
151 This time you were running the fuzzer with a non-empty input corpus (564 items).
152 As the first step, the fuzzer minimized the set to produce 344 interesting items (the ``INITED`` line)
154 You may run ``N`` independent fuzzer jobs in parallel on ``M`` CPUs::
156 N=100; M=4; ./pcre_fuzzer ./CORPUS -jobs=$N -workers=$M
158 This is useful when you already have an exhaustive test corpus.
159 If you've just started fuzzing with no good corpus running independent
160 jobs will create a corpus with too many duplicates.
161 One way to avoid this and still use all of your CPUs is to use the flag ``-exit_on_first=1``
162 which will cause the fuzzer to exit on the first new synthesised input::
164 N=100; M=4; ./pcre_fuzzer ./CORPUS -jobs=$N -workers=$M -exit_on_first=1
172 By default, the fuzzer is not aware of complexities of the input language
173 and when fuzzing e.g. a C++ parser it will mostly stress the lexer.
174 It is very hard for the fuzzer to come up with something like ``reinterpret_cast<int>``
175 from a test corpus that doesn't have it.
176 See a detailed discussion of this topic at
177 http://lcamtuf.blogspot.com/2015/01/afl-fuzz-making-up-grammar-with.html.
179 lib/Fuzzer implements a simple technique that allows to fuzz input languages with
180 long tokens. All you need is to prepare a text file containing up to 253 tokens, one token per line,
181 and pass it to the fuzzer as ``-tokens=TOKENS_FILE.txt``.
182 Three implicit tokens are added: ``" "``, ``"\t"``, and ``"\n"``.
183 The fuzzer itself will still be mutating a string of bytes
184 but before passing this input to the target library it will replace every byte ``b`` with the ``b``-th token.
185 If there are less than ``b`` tokens, a space will be added instead.
188 Fuzzing components of LLVM
189 ==========================
193 The inputs are random pieces of C++-like text.
195 Build (make sure to use fresh clang as the host compiler)::
197 cmake -GNinja -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DLLVM_USE_SANITIZER=Address -DLLVM_USE_SANITIZE_COVERAGE=YES -DCMAKE_BUILD_TYPE=Release /path/to/llvm
198 ninja clang-format-fuzzer
200 ./bin/clang-format-fuzzer CORPUS_DIR
202 Optionally build other kinds of binaries (asan+Debug, msan, ubsan, etc).
204 TODO: commit the pre-fuzzed corpus to svn (?).
206 Tracking bug: https://llvm.org/bugs/show_bug.cgi?id=23052
211 The default behavior is very similar to ``clang-format-fuzzer``.
212 Clang can also be fuzzed with Tokens_ using ``-tokens=$LLVM/lib/Fuzzer/cxx_fuzzer_tokens.txt`` option.
214 Tracking bug: https://llvm.org/bugs/show_bug.cgi?id=23057
217 =========================
219 Q. Why Fuzzer does not use any of the LLVM support?
220 ---------------------------------------------------
222 There are two reasons.
224 First, we want this library to be used outside of the LLVM w/o users having to
225 build the rest of LLVM. This may sound unconvincing for many LLVM folks,
226 but in practice the need for building the whole LLVM frightens many potential
227 users -- and we want more users to use this code.
229 Second, there is a subtle technical reason not to rely on the rest of LLVM, or
230 any other large body of code (maybe not even STL). When coverage instrumentation
231 is enabled, it will also instrument the LLVM support code which will blow up the
232 coverage set of the process (since the fuzzer is in-process). In other words, by
233 using more external dependencies we will slow down the fuzzer while the main
234 reason for it to exist is extreme speed.
236 Q. What about Windows then? The Fuzzer contains code that does not build on Windows.
237 ------------------------------------------------------------------------------------
239 The sanitizer coverage support does not work on Windows either as of 01/2015.
240 Once it's there, we'll need to re-implement OS-specific parts (I/O, signals).
242 Q. When this Fuzzer is not a good solution for a problem?
243 ---------------------------------------------------------
245 * If the test inputs are validated by the target library and the validator
246 asserts/crashes on invalid inputs, the in-process fuzzer is not applicable
247 (we could use fork() w/o exec, but it comes with extra overhead).
248 * Bugs in the target library may accumulate w/o being detected. E.g. a memory
249 corruption that goes undetected at first and then leads to a crash while
250 testing another input. This is why it is highly recommended to run this
251 in-process fuzzer with all sanitizers to detect most bugs on the spot.
252 * It is harder to protect the in-process fuzzer from excessive memory
253 consumption and infinite loops in the target library (still possible).
254 * The target library should not have significant global state that is not
255 reset between the runs.
256 * Many interesting target libs are not designed in a way that supports
257 the in-process fuzzer interface (e.g. require a file path instead of a
259 * If a single test run takes a considerable fraction of a second (or
260 more) the speed benefit from the in-process fuzzer is negligible.
261 * If the target library runs persistent threads (that outlive
262 execution of one test) the fuzzing results will be unreliable.
264 Q. So, what exactly this Fuzzer is good for?
265 --------------------------------------------
267 This Fuzzer might be a good choice for testing libraries that have relatively
268 small inputs, each input takes < 1ms to run, and the library code is not expected
269 to crash on invalid inputs.
270 Examples: regular expression matchers, text or binary format parsers.
272 .. _pcre2: http://www.pcre.org/
274 .. _AFL: http://lcamtuf.coredump.cx/afl/
276 .. _SanitizerCoverage: https://code.google.com/p/address-sanitizer/wiki/AsanCoverage