llvm/docs/LibFuzzer.rst - toolchain/llvm-project - Gitiles

 ========================================================
 LibFuzzer -- a library for coverage-guided fuzz testing.
 ========================================================
 .. contents::
    :local:
    :depth: 4

 Introduction
 ============

 This library is intended primarily for in-process coverage-guided fuzz testing
 (fuzzing) of other libraries. The typical workflow looks like this:

 * Build the Fuzzer library as a static archive (or just a set of .o files).
   Note that the Fuzzer contains the main() function.
   Preferably do *not* use sanitizers while building the Fuzzer.
 * Build the library you are going to test with
   `-fsanitize-coverage={bb,edge}[,indirect-calls,8bit-counters]`
   and one of the sanitizers. We recommend to build the library in several
   different modes (e.g. asan, msan, lsan, ubsan, etc) and even using different
   optimizations options (e.g. -O0, -O1, -O2) to diversify testing.
 * Build a test driver using the same options as the library.
   The test driver is a C/C++ file containing interesting calls to the library
   inside a single function  ``extern "C" void LLVMFuzzerTestOneInput(const uint8_t *Data, size_t Size);``
 * Link the Fuzzer, the library and the driver together into an executable
   using the same sanitizer options as for the library.
 * Collect the initial corpus of inputs for the
   fuzzer (a directory with test inputs, one file per input).
   The better your inputs are the faster you will find something interesting.
   Also try to keep your inputs small, otherwise the Fuzzer will run too slow.
   By default, the Fuzzer limits the size of every input by 64 bytes
   (use ``-max_len=N`` to override).
 * Run the fuzzer with the test corpus. As new interesting test cases are
   discovered they will be added to the corpus. If a bug is discovered by
   the sanitizer (asan, etc) it will be reported as usual and the reproducer
   will be written to disk.
   Each Fuzzer process is single-threaded (unless the library starts its own
   threads). You can run the Fuzzer on the same corpus in multiple processes
   in parallel.


 The Fuzzer is similar in concept to AFL_,
 but uses in-process Fuzzing, which is more fragile, more restrictive, but
 potentially much faster as it has no overhead for process start-up.
 It uses LLVM's SanitizerCoverage_ instrumentation to get in-process
 coverage-feedback

 The code resides in the LLVM repository, requires the fresh Clang compiler to build
 and is used to fuzz various parts of LLVM,
 but the Fuzzer itself does not (and should not) depend on any
 part of LLVM and can be used for other projects w/o requiring the rest of LLVM.

 Flags
 =====
 The most important flags are::

   seed                               	0	Random seed. If 0, seed is generated.
   runs                               	-1	Number of individual test runs (-1 for infinite runs).
   max_len                            	64	Maximal length of the test input.
   cross_over                         	1	If 1, cross over inputs.
   mutate_depth                       	5	Apply this number of consecutive mutations to each input.
   timeout                            	-1	Timeout in seconds (if positive). If one unit runs more than this number of seconds the process will abort.
   help                               	0	Print help.
   save_minimized_corpus              	0	If 1, the minimized corpus is saved into the first input directory
   jobs                               	0	Number of jobs to run. If jobs >= 1 we spawn this number of jobs in separate worker processes with stdout/stderr redirected to fuzz-JOB.log.
   workers                            	0	Number of simultaneous worker processes to run the jobs. If zero, "min(jobs,NumberOfCpuCores()/2)" is used.
   tokens                             	0	Use the file with tokens (one token per line) to fuzz a token based input language.
   apply_tokens                       	0	Read the given input file, substitute bytes  with tokens and write the result to stdout.
   sync_command                       	0	Execute an external command "<sync_command> <test_corpus>" to synchronize the test corpus.
   sync_timeout                       	600	Minimal timeout between syncs.

 For the full list of flags run the fuzzer binary with ``-help=1``.

 Usage examples
 ==============

 Toy example
 -----------

 A simple function that does something interesting if it receives the input "HI!"::

   cat << EOF >> test_fuzzer.cc
   extern "C" void LLVMFuzzerTestOneInput(const unsigned char *data, unsigned long size) {
     if (size > 0 && data[0] == 'H')
       if (size > 1 && data[1] == 'I')
          if (size > 2 && data[2] == '!')
          __builtin_trap();
   }
   EOF
   # Get lib/Fuzzer. Assuming that you already have fresh clang in PATH.
   svn co http://llvm.org/svn/llvm-project/llvm/trunk/lib/Fuzzer
   # Build lib/Fuzzer files.
   clang -c -g -O2 -std=c++11 Fuzzer/*.cpp -IFuzzer
   # Build test_fuzzer.cc with asan and link against lib/Fuzzer.
   clang++ -fsanitize=address -fsanitize-coverage=edge test_fuzzer.cc Fuzzer*.o
   # Run the fuzzer with no corpus.
   ./a.out

 You should get ``Illegal instruction (core dumped)`` pretty quickly.

 PCRE2
 -----

 Here we show how to use lib/Fuzzer on something real, yet simple: pcre2_::

   COV_FLAGS=" -fsanitize-coverage=edge,indirect-calls,8bit-counters"
   # Get PCRE2
   svn co svn://vcs.exim.org/pcre2/code/trunk pcre
   # Get lib/Fuzzer. Assuming that you already have fresh clang in PATH.
   svn co http://llvm.org/svn/llvm-project/llvm/trunk/lib/Fuzzer
   # Build PCRE2 with AddressSanitizer and coverage.
   (cd pcre; ./autogen.sh; CC="clang -fsanitize=address $COV_FLAGS" ./configure --prefix=`pwd`/../inst && make -j && make install)
   # Build lib/Fuzzer files.
   clang -c -g -O2 -std=c++11 Fuzzer/*.cpp -IFuzzer
   # Build the the actual function that does something interesting with PCRE2.
   cat << EOF > pcre_fuzzer.cc
   #include <string.h>
   #include "pcre2posix.h"
   extern "C" void LLVMFuzzerTestOneInput(const unsigned char *data, size_t size) {
     if (size < 1) return;
     char *str = new char[size+1];
     memcpy(str, data, size);
     str[size] = 0;
     regex_t preg;
     if (0 == regcomp(&preg, str, 0)) {
       regexec(&preg, str, 0, 0, 0);
       regfree(&preg);
     }
     delete [] str;
   }
   EOF
   clang++ -g -fsanitize=address $COV_FLAGS -c -std=c++11  -I inst/include/ pcre_fuzzer.cc
   # Link.
   clang++ -g -fsanitize=address -Wl,--whole-archive inst/lib/*.a -Wl,-no-whole-archive Fuzzer*.o pcre_fuzzer.o -o pcre_fuzzer

 This will give you a binary of the fuzzer, called ``pcre_fuzzer``.
 Now, create a directory that will hold the test corpus::

   mkdir -p CORPUS

 For simple input languages like regular expressions this is all you need.
 For more complicated inputs populate the directory with some input samples.
 Now run the fuzzer with the corpus dir as the only parameter::

   ./pcre_fuzzer ./CORPUS

 You will see output like this::

   Seed: 1876794929
   #0      READ   cov 0 bits 0 units 1 exec/s 0
   #1      pulse  cov 3 bits 0 units 1 exec/s 0
   #1      INITED cov 3 bits 0 units 1 exec/s 0
   #2      pulse  cov 208 bits 0 units 1 exec/s 0
   #2      NEW    cov 208 bits 0 units 2 exec/s 0 L: 64
   #3      NEW    cov 217 bits 0 units 3 exec/s 0 L: 63
   #4      pulse  cov 217 bits 0 units 3 exec/s 0

 * The ``Seed:`` line shows you the current random seed (you can change it with ``-seed=N`` flag).
 * 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).
 * The ``INITED`` line shows you that how many inputs will be fuzzed.
 * 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.
 * The ``pulse`` lines appear periodically to show the current status.

 Now, interrupt the fuzzer and run it again the same way. You will see::

   Seed: 1879995378
   #0      READ   cov 0 bits 0 units 564 exec/s 0
   #1      pulse  cov 502 bits 0 units 564 exec/s 0
   ...
   #512    pulse  cov 2933 bits 0 units 564 exec/s 512
   #564    INITED cov 2991 bits 0 units 344 exec/s 564
   #1024   pulse  cov 2991 bits 0 units 344 exec/s 1024
   #1455   NEW    cov 2995 bits 0 units 345 exec/s 1455 L: 49

 This time you were running the fuzzer with a non-empty input corpus (564 items).
 As the first step, the fuzzer minimized the set to produce 344 interesting items (the ``INITED`` line)

 It is quite convenient to store test corpuses in git.
 As an example, here is a git repository with test inputs for the above PCRE2 fuzzer::

   git clone https://github.com/kcc/fuzzing-with-sanitizers.git
   ./pcre_fuzzer ./fuzzing-with-sanitizers/pcre2/C1/

 You may run ``N`` independent fuzzer jobs in parallel on ``M`` CPUs::

   N=100; M=4; ./pcre_fuzzer ./CORPUS -jobs=$N -workers=$M

 By default (``-reload=1``) the fuzzer processes will periodically scan the CORPUS directory
 and reload any new tests. This way the test inputs found by one process will be picked up
 by all others.

 If ``-workers=$M`` is not supplied, ``min($N,NumberOfCpuCore/2)`` will be used.

 Heartbleed
 ----------
 Remember Heartbleed_?
 As it was recently `shown <https://blog.hboeck.de/archives/868-How-Heartbleed-couldve-been-found.html>`_,
 fuzzing with AddressSanitizer can find Heartbleed. Indeed, here are the step-by-step instructions
 to find Heartbleed with LibFuzzer::

   wget https://www.openssl.org/source/openssl-1.0.1f.tar.gz
   tar xf openssl-1.0.1f.tar.gz
   COV_FLAGS="-fsanitize-coverage=edge,indirect-calls" # -fsanitize-coverage=8bit-counters
   (cd openssl-1.0.1f/ && ./config &&
     make -j 32 CC="clang -g -fsanitize=address $COV_FLAGS")
   # Get and build LibFuzzer
   svn co http://llvm.org/svn/llvm-project/llvm/trunk/lib/Fuzzer
   clang -c -g -O2 -std=c++11 Fuzzer/*.cpp -IFuzzer
   # Get examples of key/pem files.
   git clone   https://github.com/hannob/selftls
   cp selftls/server* . -v
   cat << EOF > handshake-fuzz.cc
   #include <openssl/ssl.h>
   #include <openssl/err.h>
   #include <assert.h>
   SSL_CTX *sctx;
   int Init() {
     SSL_library_init();
     SSL_load_error_strings();
     ERR_load_BIO_strings();
     OpenSSL_add_all_algorithms();
     assert (sctx = SSL_CTX_new(TLSv1_method()));
     assert (SSL_CTX_use_certificate_file(sctx, "server.pem", SSL_FILETYPE_PEM));
     assert (SSL_CTX_use_PrivateKey_file(sctx, "server.key", SSL_FILETYPE_PEM));
     return 0;
   }
   extern "C" void LLVMFuzzerTestOneInput(unsigned char *Data, size_t Size) {
     static int unused = Init();
     SSL *server = SSL_new(sctx);
     BIO *sinbio = BIO_new(BIO_s_mem());
     BIO *soutbio = BIO_new(BIO_s_mem());
     SSL_set_bio(server, sinbio, soutbio);
     SSL_set_accept_state(server);
     BIO_write(sinbio, Data, Size);
     SSL_do_handshake(server);
     SSL_free(server);
   }
   EOF
   # Build the fuzzer.
   clang++ -g handshake-fuzz.cc  -fsanitize=address \
     openssl-1.0.1f/libssl.a openssl-1.0.1f/libcrypto.a Fuzzer*.o
   # Run 20 independent fuzzer jobs.
   ./a.out  -jobs=20 -workers=20

 Voila::

   #1048576        pulse  cov 3424 bits 0 units 9 exec/s 24385
   =================================================================
   ==17488==ERROR: AddressSanitizer: heap-buffer-overflow on address 0x629000004748 at pc 0x00000048c979 bp 0x7fffe3e864f0 sp 0x7fffe3e85ca8
   READ of size 60731 at 0x629000004748 thread T0
       #0 0x48c978 in __asan_memcpy
       #1 0x4db504 in tls1_process_heartbeat openssl-1.0.1f/ssl/t1_lib.c:2586:3
       #2 0x580be3 in ssl3_read_bytes openssl-1.0.1f/ssl/s3_pkt.c:1092:4

 Advanced features
 =================

 Tokens
 ------

 By default, the fuzzer is not aware of complexities of the input language
 and when fuzzing e.g. a C++ parser it will mostly stress the lexer.
 It is very hard for the fuzzer to come up with something like ``reinterpret_cast<int>``
 from a test corpus that doesn't have it.
 See a detailed discussion of this topic at
 http://lcamtuf.blogspot.com/2015/01/afl-fuzz-making-up-grammar-with.html.

 lib/Fuzzer implements a simple technique that allows to fuzz input languages with
 long tokens. All you need is to prepare a text file containing up to 253 tokens, one token per line,
 and pass it to the fuzzer as ``-tokens=TOKENS_FILE.txt``.
 Three implicit tokens are added: ``" "``, ``"\t"``, and ``"\n"``.
 The fuzzer itself will still be mutating a string of bytes
 but before passing this input to the target library it will replace every byte ``b`` with the ``b``-th token.
 If there are less than ``b`` tokens, a space will be added instead.

 AFL compatibility
 -----------------
 LibFuzzer can be used in parallel with AFL_ on the same test corpus.
 Both fuzzers expect the test corpus to reside in a directory, one file per input.
 You can run both fuzzers on the same corpus in parallel::

   ./afl-fuzz -i testcase_dir -o findings_dir /path/to/program -r @@
   ./llvm-fuzz testcase_dir findings_dir  # Will write new tests to testcase_dir

 Periodically restart both fuzzers so that they can use each other's findings.

 How good is my fuzzer?
 ----------------------

 Once you implement your target function ``LLVMFuzzerTestOneInput`` and fuzz it to death,
 you will want to know whether the function or the corpus can be improved further.
 One easy to use metric is, of course, code coverage.
 You can get the coverage for your corpus like this::

   ASAN_OPTIONS=coverage_pcs=1 ./fuzzer CORPUS_DIR -runs=0

 This will run all the tests in the CORPUS_DIR but will not generate any new tests
 and dump covered PCs to disk before exiting.
 Then you can subtract the set of covered PCs from the set of all instrumented PCs in the binary,
 see SanitizerCoverage_ for details.

 User-supplied mutators
 ----------------------

 LibFuzzer allows to use custom (user-supplied) mutators,
 see FuzzerInterface.h_

 Fuzzing components of LLVM
 ==========================

 clang-format-fuzzer
 -------------------
 The inputs are random pieces of C++-like text.

 Build (make sure to use fresh clang as the host compiler)::

     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
     ninja clang-format-fuzzer
     mkdir CORPUS_DIR
     ./bin/clang-format-fuzzer CORPUS_DIR

 Optionally build other kinds of binaries (asan+Debug, msan, ubsan, etc).

 TODO: commit the pre-fuzzed corpus to svn (?).

 Tracking bug: https://llvm.org/bugs/show_bug.cgi?id=23052

 clang-fuzzer
 ------------

 The default behavior is very similar to ``clang-format-fuzzer``.
 Clang can also be fuzzed with Tokens_ using ``-tokens=$LLVM/lib/Fuzzer/cxx_fuzzer_tokens.txt`` option.

 Tracking bug: https://llvm.org/bugs/show_bug.cgi?id=23057

 Buildbot
 --------

 We have a buildbot that runs the above fuzzers for LLVM components
 24/7/365 at http://lab.llvm.org:8011/builders/sanitizer-x86_64-linux-fuzzer .

 Pre-fuzzed test inputs in git
 -----------------------------

 The buildbot occumulates large test corpuses over time.
 The corpuses are stored in git on github and can be used like this::

   git clone https://github.com/kcc/fuzzing-with-sanitizers.git
   bin/clang-format-fuzzer fuzzing-with-sanitizers/llvm/clang-format/C1
   bin/clang-fuzzer        fuzzing-with-sanitizers/llvm/clang/C1/
   bin/clang-fuzzer        fuzzing-with-sanitizers/llvm/clang/TOK1  -tokens=$LLVM/llvm/lib/Fuzzer/cxx_fuzzer_tokens.txt


 FAQ
 =========================

 Q. Why Fuzzer does not use any of the LLVM support?
 ---------------------------------------------------

 There are two reasons.

 First, we want this library to be used outside of the LLVM w/o users having to
 build the rest of LLVM. This may sound unconvincing for many LLVM folks,
 but in practice the need for building the whole LLVM frightens many potential
 users -- and we want more users to use this code.

 Second, there is a subtle technical reason not to rely on the rest of LLVM, or
 any other large body of code (maybe not even STL). When coverage instrumentation
 is enabled, it will also instrument the LLVM support code which will blow up the
 coverage set of the process (since the fuzzer is in-process). In other words, by
 using more external dependencies we will slow down the fuzzer while the main
 reason for it to exist is extreme speed.

 Q. What about Windows then? The Fuzzer contains code that does not build on Windows.
 ------------------------------------------------------------------------------------

 The sanitizer coverage support does not work on Windows either as of 01/2015.
 Once it's there, we'll need to re-implement OS-specific parts (I/O, signals).

 Q. When this Fuzzer is not a good solution for a problem?
 ---------------------------------------------------------

 * If the test inputs are validated by the target library and the validator
   asserts/crashes on invalid inputs, the in-process fuzzer is not applicable
   (we could use fork() w/o exec, but it comes with extra overhead).
 * Bugs in the target library may accumulate w/o being detected. E.g. a memory
   corruption that goes undetected at first and then leads to a crash while
   testing another input. This is why it is highly recommended to run this
   in-process fuzzer with all sanitizers to detect most bugs on the spot.
 * It is harder to protect the in-process fuzzer from excessive memory
   consumption and infinite loops in the target library (still possible).
 * The target library should not have significant global state that is not
   reset between the runs.
 * Many interesting target libs are not designed in a way that supports
   the in-process fuzzer interface (e.g. require a file path instead of a
   byte array).
 * If a single test run takes a considerable fraction of a second (or
   more) the speed benefit from the in-process fuzzer is negligible.
 * If the target library runs persistent threads (that outlive
   execution of one test) the fuzzing results will be unreliable.

 Q. So, what exactly this Fuzzer is good for?
 --------------------------------------------

 This Fuzzer might be a good choice for testing libraries that have relatively
 small inputs, each input takes < 1ms to run, and the library code is not expected
 to crash on invalid inputs.
 Examples: regular expression matchers, text or binary format parsers.

 .. _pcre2: http://www.pcre.org/

 .. _AFL: http://lcamtuf.coredump.cx/afl/

 .. _SanitizerCoverage: http://clang.llvm.org/docs/SanitizerCoverage.html

 .. _Heartbleed: http://en.wikipedia.org/wiki/Heartbleed

 .. _FuzzerInterface.h: https://github.com/llvm-mirror/llvm/blob/master/lib/Fuzzer/FuzzerInterface.h
	========================================================
	LibFuzzer -- a library for coverage-guided fuzz testing.
	========================================================
	.. contents::
	:local:
	:depth: 4

	Introduction
	============

	This library is intended primarily for in-process coverage-guided fuzz testing
	(fuzzing) of other libraries. The typical workflow looks like this:

	* Build the Fuzzer library as a static archive (or just a set of .o files).
	Note that the Fuzzer contains the main() function.
	Preferably do not use sanitizers while building the Fuzzer.
	* Build the library you are going to test with
	`-fsanitize-coverage={bb,edge}[,indirect-calls,8bit-counters]`
	and one of the sanitizers. We recommend to build the library in several
	different modes (e.g. asan, msan, lsan, ubsan, etc) and even using different
	optimizations options (e.g. -O0, -O1, -O2) to diversify testing.
	* Build a test driver using the same options as the library.
	The test driver is a C/C++ file containing interesting calls to the library
	inside a single function ``extern "C" void LLVMFuzzerTestOneInput(const uint8_t *Data, size_t Size);``
	* Link the Fuzzer, the library and the driver together into an executable
	using the same sanitizer options as for the library.
	* Collect the initial corpus of inputs for the
	fuzzer (a directory with test inputs, one file per input).
	The better your inputs are the faster you will find something interesting.
	Also try to keep your inputs small, otherwise the Fuzzer will run too slow.
	By default, the Fuzzer limits the size of every input by 64 bytes
	(use ``-max_len=N`` to override).
	* Run the fuzzer with the test corpus. As new interesting test cases are
	discovered they will be added to the corpus. If a bug is discovered by
	the sanitizer (asan, etc) it will be reported as usual and the reproducer
	will be written to disk.
	Each Fuzzer process is single-threaded (unless the library starts its own
	threads). You can run the Fuzzer on the same corpus in multiple processes
	in parallel.


	The Fuzzer is similar in concept to AFL_,
	but uses in-process Fuzzing, which is more fragile, more restrictive, but
	potentially much faster as it has no overhead for process start-up.
	It uses LLVM's SanitizerCoverage_ instrumentation to get in-process
	coverage-feedback

	The code resides in the LLVM repository, requires the fresh Clang compiler to build
	and is used to fuzz various parts of LLVM,
	but the Fuzzer itself does not (and should not) depend on any
	part of LLVM and can be used for other projects w/o requiring the rest of LLVM.

	Flags
	=====
	The most important flags are::

	seed 0 Random seed. If 0, seed is generated.
	runs -1 Number of individual test runs (-1 for infinite runs).
	max_len 64 Maximal length of the test input.
	cross_over 1 If 1, cross over inputs.
	mutate_depth 5 Apply this number of consecutive mutations to each input.
	timeout -1 Timeout in seconds (if positive). If one unit runs more than this number of seconds the process will abort.
	help 0 Print help.
	save_minimized_corpus 0 If 1, the minimized corpus is saved into the first input directory
	jobs 0 Number of jobs to run. If jobs >= 1 we spawn this number of jobs in separate worker processes with stdout/stderr redirected to fuzz-JOB.log.
	workers 0 Number of simultaneous worker processes to run the jobs. If zero, "min(jobs,NumberOfCpuCores()/2)" is used.
	tokens 0 Use the file with tokens (one token per line) to fuzz a token based input language.
	apply_tokens 0 Read the given input file, substitute bytes with tokens and write the result to stdout.
	sync_command 0 Execute an external command "<sync_command> <test_corpus>" to synchronize the test corpus.
	sync_timeout 600 Minimal timeout between syncs.

	For the full list of flags run the fuzzer binary with ``-help=1``.

	Usage examples
	==============

	Toy example
	-----------

	A simple function that does something interesting if it receives the input "HI!"::

	cat << EOF >> test_fuzzer.cc
	extern "C" void LLVMFuzzerTestOneInput(const unsigned char *data, unsigned long size) {
	if (size > 0 && data[0] == 'H')
	if (size > 1 && data[1] == 'I')
	if (size > 2 && data[2] == '!')
	__builtin_trap();
	}
	EOF
	# Get lib/Fuzzer. Assuming that you already have fresh clang in PATH.
	svn co http://llvm.org/svn/llvm-project/llvm/trunk/lib/Fuzzer
	# Build lib/Fuzzer files.
	clang -c -g -O2 -std=c++11 Fuzzer/*.cpp -IFuzzer
	# Build test_fuzzer.cc with asan and link against lib/Fuzzer.
	clang++ -fsanitize=address -fsanitize-coverage=edge test_fuzzer.cc Fuzzer*.o
	# Run the fuzzer with no corpus.
	./a.out

	You should get ``Illegal instruction (core dumped)`` pretty quickly.

	PCRE2
	-----

	Here we show how to use lib/Fuzzer on something real, yet simple: pcre2_::

	COV_FLAGS=" -fsanitize-coverage=edge,indirect-calls,8bit-counters"
	# Get PCRE2
	svn co svn://vcs.exim.org/pcre2/code/trunk pcre
	# Get lib/Fuzzer. Assuming that you already have fresh clang in PATH.
	svn co http://llvm.org/svn/llvm-project/llvm/trunk/lib/Fuzzer
	# Build PCRE2 with AddressSanitizer and coverage.
	(cd pcre; ./autogen.sh; CC="clang -fsanitize=address $COV_FLAGS" ./configure --prefix=`pwd`/../inst && make -j && make install)
	# Build lib/Fuzzer files.
	clang -c -g -O2 -std=c++11 Fuzzer/*.cpp -IFuzzer
	# Build the the actual function that does something interesting with PCRE2.
	cat << EOF > pcre_fuzzer.cc
	#include <string.h>
	#include "pcre2posix.h"
	extern "C" void LLVMFuzzerTestOneInput(const unsigned char *data, size_t size) {
	if (size < 1) return;
	char *str = new char[size+1];
	memcpy(str, data, size);
	str[size] = 0;
	regex_t preg;
	if (0 == regcomp(&preg, str, 0)) {
	regexec(&preg, str, 0, 0, 0);
	regfree(&preg);
	}
	delete [] str;
	}
	EOF
	clang++ -g -fsanitize=address $COV_FLAGS -c -std=c++11 -I inst/include/ pcre_fuzzer.cc
	# Link.
	clang++ -g -fsanitize=address -Wl,--whole-archive inst/lib/.a -Wl,-no-whole-archive Fuzzer.o pcre_fuzzer.o -o pcre_fuzzer

	This will give you a binary of the fuzzer, called ``pcre_fuzzer``.
	Now, create a directory that will hold the test corpus::

	mkdir -p CORPUS

	For simple input languages like regular expressions this is all you need.
	For more complicated inputs populate the directory with some input samples.
	Now run the fuzzer with the corpus dir as the only parameter::

	./pcre_fuzzer ./CORPUS

	You will see output like this::

	Seed: 1876794929
	#0 READ cov 0 bits 0 units 1 exec/s 0
	#1 pulse cov 3 bits 0 units 1 exec/s 0
	#1 INITED cov 3 bits 0 units 1 exec/s 0
	#2 pulse cov 208 bits 0 units 1 exec/s 0
	#2 NEW cov 208 bits 0 units 2 exec/s 0 L: 64
	#3 NEW cov 217 bits 0 units 3 exec/s 0 L: 63
	#4 pulse cov 217 bits 0 units 3 exec/s 0

	* The ``Seed:`` line shows you the current random seed (you can change it with ``-seed=N`` flag).
	* 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).
	* The ``INITED`` line shows you that how many inputs will be fuzzed.
	* 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.
	* The ``pulse`` lines appear periodically to show the current status.

	Now, interrupt the fuzzer and run it again the same way. You will see::

	Seed: 1879995378
	#0 READ cov 0 bits 0 units 564 exec/s 0
	#1 pulse cov 502 bits 0 units 564 exec/s 0
	...
	#512 pulse cov 2933 bits 0 units 564 exec/s 512
	#564 INITED cov 2991 bits 0 units 344 exec/s 564
	#1024 pulse cov 2991 bits 0 units 344 exec/s 1024
	#1455 NEW cov 2995 bits 0 units 345 exec/s 1455 L: 49

	This time you were running the fuzzer with a non-empty input corpus (564 items).
	As the first step, the fuzzer minimized the set to produce 344 interesting items (the ``INITED`` line)

	It is quite convenient to store test corpuses in git.
	As an example, here is a git repository with test inputs for the above PCRE2 fuzzer::

	git clone https://github.com/kcc/fuzzing-with-sanitizers.git
	./pcre_fuzzer ./fuzzing-with-sanitizers/pcre2/C1/

	You may run ``N`` independent fuzzer jobs in parallel on ``M`` CPUs::

	N=100; M=4; ./pcre_fuzzer ./CORPUS -jobs=$N -workers=$M

	By default (``-reload=1``) the fuzzer processes will periodically scan the CORPUS directory
	and reload any new tests. This way the test inputs found by one process will be picked up
	by all others.

	If ``-workers=$M`` is not supplied, ``min($N,NumberOfCpuCore/2)`` will be used.

	Heartbleed
	----------
	Remember Heartbleed_?
	As it was recently `shown <https://blog.hboeck.de/archives/868-How-Heartbleed-couldve-been-found.html>`_,
	fuzzing with AddressSanitizer can find Heartbleed. Indeed, here are the step-by-step instructions
	to find Heartbleed with LibFuzzer::

	wget https://www.openssl.org/source/openssl-1.0.1f.tar.gz
	tar xf openssl-1.0.1f.tar.gz
	COV_FLAGS="-fsanitize-coverage=edge,indirect-calls" # -fsanitize-coverage=8bit-counters
	(cd openssl-1.0.1f/ && ./config &&
	make -j 32 CC="clang -g -fsanitize=address $COV_FLAGS")
	# Get and build LibFuzzer
	svn co http://llvm.org/svn/llvm-project/llvm/trunk/lib/Fuzzer
	clang -c -g -O2 -std=c++11 Fuzzer/*.cpp -IFuzzer
	# Get examples of key/pem files.
	git clone https://github.com/hannob/selftls
	cp selftls/server* . -v
	cat << EOF > handshake-fuzz.cc
	#include <openssl/ssl.h>
	#include <openssl/err.h>
	#include <assert.h>
	SSL_CTX *sctx;
	int Init() {
	SSL_library_init();
	SSL_load_error_strings();
	ERR_load_BIO_strings();
	OpenSSL_add_all_algorithms();
	assert (sctx = SSL_CTX_new(TLSv1_method()));
	assert (SSL_CTX_use_certificate_file(sctx, "server.pem", SSL_FILETYPE_PEM));
	assert (SSL_CTX_use_PrivateKey_file(sctx, "server.key", SSL_FILETYPE_PEM));
	return 0;
	}
	extern "C" void LLVMFuzzerTestOneInput(unsigned char *Data, size_t Size) {
	static int unused = Init();
	SSL *server = SSL_new(sctx);
	BIO *sinbio = BIO_new(BIO_s_mem());
	BIO *soutbio = BIO_new(BIO_s_mem());
	SSL_set_bio(server, sinbio, soutbio);
	SSL_set_accept_state(server);
	BIO_write(sinbio, Data, Size);
	SSL_do_handshake(server);
	SSL_free(server);
	}
	EOF
	# Build the fuzzer.
	clang++ -g handshake-fuzz.cc -fsanitize=address \
	openssl-1.0.1f/libssl.a openssl-1.0.1f/libcrypto.a Fuzzer*.o
	# Run 20 independent fuzzer jobs.
	./a.out -jobs=20 -workers=20

	Voila::

	#1048576 pulse cov 3424 bits 0 units 9 exec/s 24385
	=================================================================
	==17488==ERROR: AddressSanitizer: heap-buffer-overflow on address 0x629000004748 at pc 0x00000048c979 bp 0x7fffe3e864f0 sp 0x7fffe3e85ca8
	READ of size 60731 at 0x629000004748 thread T0
	#0 0x48c978 in __asan_memcpy
	#1 0x4db504 in tls1_process_heartbeat openssl-1.0.1f/ssl/t1_lib.c:2586:3
	#2 0x580be3 in ssl3_read_bytes openssl-1.0.1f/ssl/s3_pkt.c:1092:4

	Advanced features
	=================

	Tokens
	------

	By default, the fuzzer is not aware of complexities of the input language
	and when fuzzing e.g. a C++ parser it will mostly stress the lexer.
	It is very hard for the fuzzer to come up with something like ``reinterpret_cast<int>``
	from a test corpus that doesn't have it.
	See a detailed discussion of this topic at
	http://lcamtuf.blogspot.com/2015/01/afl-fuzz-making-up-grammar-with.html.

	lib/Fuzzer implements a simple technique that allows to fuzz input languages with
	long tokens. All you need is to prepare a text file containing up to 253 tokens, one token per line,
	and pass it to the fuzzer as ``-tokens=TOKENS_FILE.txt``.
	Three implicit tokens are added: ``" "``, ``"\t"``, and ``"\n"``.
	The fuzzer itself will still be mutating a string of bytes
	but before passing this input to the target library it will replace every byte ``b`` with the ``b``-th token.
	If there are less than ``b`` tokens, a space will be added instead.

	AFL compatibility
	-----------------
	LibFuzzer can be used in parallel with AFL_ on the same test corpus.
	Both fuzzers expect the test corpus to reside in a directory, one file per input.
	You can run both fuzzers on the same corpus in parallel::

	./afl-fuzz -i testcase_dir -o findings_dir /path/to/program -r @@
	./llvm-fuzz testcase_dir findings_dir # Will write new tests to testcase_dir

	Periodically restart both fuzzers so that they can use each other's findings.

	How good is my fuzzer?
	----------------------

	Once you implement your target function ``LLVMFuzzerTestOneInput`` and fuzz it to death,
	you will want to know whether the function or the corpus can be improved further.
	One easy to use metric is, of course, code coverage.
	You can get the coverage for your corpus like this::

	ASAN_OPTIONS=coverage_pcs=1 ./fuzzer CORPUS_DIR -runs=0

	This will run all the tests in the CORPUS_DIR but will not generate any new tests
	and dump covered PCs to disk before exiting.
	Then you can subtract the set of covered PCs from the set of all instrumented PCs in the binary,
	see SanitizerCoverage_ for details.

	User-supplied mutators
	----------------------

	LibFuzzer allows to use custom (user-supplied) mutators,
	see FuzzerInterface.h_

	Fuzzing components of LLVM
	==========================

	clang-format-fuzzer
	-------------------
	The inputs are random pieces of C++-like text.

	Build (make sure to use fresh clang as the host compiler)::

	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
	ninja clang-format-fuzzer
	mkdir CORPUS_DIR
	./bin/clang-format-fuzzer CORPUS_DIR

	Optionally build other kinds of binaries (asan+Debug, msan, ubsan, etc).

	TODO: commit the pre-fuzzed corpus to svn (?).

	Tracking bug: https://llvm.org/bugs/show_bug.cgi?id=23052

	clang-fuzzer
	------------

	The default behavior is very similar to ``clang-format-fuzzer``.
	Clang can also be fuzzed with Tokens_ using ``-tokens=$LLVM/lib/Fuzzer/cxx_fuzzer_tokens.txt`` option.

	Tracking bug: https://llvm.org/bugs/show_bug.cgi?id=23057

	Buildbot
	--------

	We have a buildbot that runs the above fuzzers for LLVM components
	24/7/365 at http://lab.llvm.org:8011/builders/sanitizer-x86_64-linux-fuzzer .

	Pre-fuzzed test inputs in git
	-----------------------------

	The buildbot occumulates large test corpuses over time.
	The corpuses are stored in git on github and can be used like this::

	git clone https://github.com/kcc/fuzzing-with-sanitizers.git
	bin/clang-format-fuzzer fuzzing-with-sanitizers/llvm/clang-format/C1
	bin/clang-fuzzer fuzzing-with-sanitizers/llvm/clang/C1/
	bin/clang-fuzzer fuzzing-with-sanitizers/llvm/clang/TOK1 -tokens=$LLVM/llvm/lib/Fuzzer/cxx_fuzzer_tokens.txt


	FAQ
	=========================

	Q. Why Fuzzer does not use any of the LLVM support?
	---------------------------------------------------

	There are two reasons.

	First, we want this library to be used outside of the LLVM w/o users having to
	build the rest of LLVM. This may sound unconvincing for many LLVM folks,
	but in practice the need for building the whole LLVM frightens many potential
	users -- and we want more users to use this code.

	Second, there is a subtle technical reason not to rely on the rest of LLVM, or
	any other large body of code (maybe not even STL). When coverage instrumentation
	is enabled, it will also instrument the LLVM support code which will blow up the
	coverage set of the process (since the fuzzer is in-process). In other words, by
	using more external dependencies we will slow down the fuzzer while the main
	reason for it to exist is extreme speed.

	Q. What about Windows then? The Fuzzer contains code that does not build on Windows.
	------------------------------------------------------------------------------------

	The sanitizer coverage support does not work on Windows either as of 01/2015.
	Once it's there, we'll need to re-implement OS-specific parts (I/O, signals).

	Q. When this Fuzzer is not a good solution for a problem?
	---------------------------------------------------------

	* If the test inputs are validated by the target library and the validator
	asserts/crashes on invalid inputs, the in-process fuzzer is not applicable
	(we could use fork() w/o exec, but it comes with extra overhead).
	* Bugs in the target library may accumulate w/o being detected. E.g. a memory
	corruption that goes undetected at first and then leads to a crash while
	testing another input. This is why it is highly recommended to run this
	in-process fuzzer with all sanitizers to detect most bugs on the spot.
	* It is harder to protect the in-process fuzzer from excessive memory
	consumption and infinite loops in the target library (still possible).
	* The target library should not have significant global state that is not
	reset between the runs.
	* Many interesting target libs are not designed in a way that supports
	the in-process fuzzer interface (e.g. require a file path instead of a
	byte array).
	* If a single test run takes a considerable fraction of a second (or
	more) the speed benefit from the in-process fuzzer is negligible.
	* If the target library runs persistent threads (that outlive
	execution of one test) the fuzzing results will be unreliable.

	Q. So, what exactly this Fuzzer is good for?
	--------------------------------------------

	This Fuzzer might be a good choice for testing libraries that have relatively
	small inputs, each input takes < 1ms to run, and the library code is not expected
	to crash on invalid inputs.
	Examples: regular expression matchers, text or binary format parsers.

	.. _pcre2: http://www.pcre.org/

	.. _AFL: http://lcamtuf.coredump.cx/afl/

	.. _SanitizerCoverage: http://clang.llvm.org/docs/SanitizerCoverage.html

	.. _Heartbleed: http://en.wikipedia.org/wiki/Heartbleed

	.. _FuzzerInterface.h: https://github.com/llvm-mirror/llvm/blob/master/lib/Fuzzer/FuzzerInterface.h