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366 lines
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ReStructuredText
========================================================
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LibFuzzer -- a library for coverage-guided fuzz testing.
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========================================================
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.. contents::
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:local:
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:depth: 4
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Introduction
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============
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This library is intended primarily for in-process coverage-guided fuzz testing
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(fuzzing) of other libraries. The typical workflow looks like this:
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* Build the Fuzzer library as a static archive (or just a set of .o files).
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Note that the Fuzzer contains the main() function.
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Preferably do *not* use sanitizers while building the Fuzzer.
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* Build the library you are going to test with
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`-fsanitize-coverage={bb,edge}[,indirect-calls]`
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and one of the sanitizers. We recommend to build the library in several
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different modes (e.g. asan, msan, lsan, ubsan, etc) and even using different
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optimizations options (e.g. -O0, -O1, -O2) to diversify testing.
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* Build a test driver using the same options as the library.
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The test driver is a C/C++ file containing interesting calls to the library
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inside a single function ``extern "C" void LLVMFuzzerTestOneInput(const uint8_t *Data, size_t Size);``
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* Link the Fuzzer, the library and the driver together into an executable
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using the same sanitizer options as for the library.
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* Collect the initial corpus of inputs for the
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fuzzer (a directory with test inputs, one file per input).
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The better your inputs are the faster you will find something interesting.
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Also try to keep your inputs small, otherwise the Fuzzer will run too slow.
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* Run the fuzzer with the test corpus. As new interesting test cases are
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discovered they will be added to the corpus. If a bug is discovered by
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the sanitizer (asan, etc) it will be reported as usual and the reproducer
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will be written to disk.
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Each Fuzzer process is single-threaded (unless the library starts its own
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threads). You can run the Fuzzer on the same corpus in multiple processes
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in parallel. For run-time options run the Fuzzer binary with '-help=1'.
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The Fuzzer is similar in concept to AFL_,
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but uses in-process Fuzzing, which is more fragile, more restrictive, but
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potentially much faster as it has no overhead for process start-up.
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It uses LLVM's SanitizerCoverage_ instrumentation to get in-process
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coverage-feedback
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The code resides in the LLVM repository, requires the fresh Clang compiler to build
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and is used to fuzz various parts of LLVM,
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but the Fuzzer itself does not (and should not) depend on any
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part of LLVM and can be used for other projects w/o requiring the rest of LLVM.
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Usage examples
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==============
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Toy example
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-----------
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A simple function that does something interesting if it receives the input "HI!"::
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cat << EOF >> test_fuzzer.cc
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extern "C" void LLVMFuzzerTestOneInput(const unsigned char *data, unsigned long size) {
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if (size > 0 && data[0] == 'H')
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if (size > 1 && data[1] == 'I')
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if (size > 2 && data[2] == '!')
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__builtin_trap();
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}
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EOF
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# Get lib/Fuzzer. Assuming that you already have fresh clang in PATH.
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svn co http://llvm.org/svn/llvm-project/llvm/trunk/lib/Fuzzer
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# Build lib/Fuzzer files.
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clang -c -g -O2 -std=c++11 Fuzzer/*.cpp -IFuzzer
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# Build test_fuzzer.cc with asan and link against lib/Fuzzer.
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clang++ -fsanitize=address -fsanitize-coverage=edge test_fuzzer.cc Fuzzer*.o
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# Run the fuzzer with no corpus.
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./a.out
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You should get ``Illegal instruction (core dumped)`` pretty quickly.
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PCRE2
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-----
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Here we show how to use lib/Fuzzer on something real, yet simple: pcre2_::
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COV_FLAGS=" -fsanitize-coverage=edge,indirect-calls,8bit-counters"
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# Get PCRE2
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svn co svn://vcs.exim.org/pcre2/code/trunk pcre
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# Get lib/Fuzzer. Assuming that you already have fresh clang in PATH.
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svn co http://llvm.org/svn/llvm-project/llvm/trunk/lib/Fuzzer
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# Build PCRE2 with AddressSanitizer and coverage.
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(cd pcre; ./autogen.sh; CC="clang -fsanitize=address $COV_FLAGS" ./configure --prefix=`pwd`/../inst && make -j && make install)
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# Build lib/Fuzzer files.
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clang -c -g -O2 -std=c++11 Fuzzer/*.cpp -IFuzzer
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# Build the the actual function that does something interesting with PCRE2.
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cat << EOF > pcre_fuzzer.cc
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#include <string.h>
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#include "pcre2posix.h"
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extern "C" void LLVMFuzzerTestOneInput(const unsigned char *data, size_t size) {
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if (size < 1) return;
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char *str = new char[size+1];
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memcpy(str, data, size);
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str[size] = 0;
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regex_t preg;
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if (0 == regcomp(&preg, str, 0)) {
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regexec(&preg, str, 0, 0, 0);
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regfree(&preg);
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}
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delete [] str;
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}
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EOF
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clang++ -g -fsanitize=address $COV_FLAGS -c -std=c++11 -I inst/include/ pcre_fuzzer.cc
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# Link.
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clang++ -g -fsanitize=address -Wl,--whole-archive inst/lib/*.a -Wl,-no-whole-archive Fuzzer*.o pcre_fuzzer.o -o pcre_fuzzer
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This will give you a binary of the fuzzer, called ``pcre_fuzzer``.
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Now, create a directory that will hold the test corpus::
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mkdir -p CORPUS
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For simple input languages like regular expressions this is all you need.
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For more complicated inputs populate the directory with some input samples.
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Now run the fuzzer with the corpus dir as the only parameter::
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./pcre_fuzzer ./CORPUS
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You will see output like this::
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Seed: 1876794929
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#0 READ cov 0 bits 0 units 1 exec/s 0
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#1 pulse cov 3 bits 0 units 1 exec/s 0
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#1 INITED cov 3 bits 0 units 1 exec/s 0
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#2 pulse cov 208 bits 0 units 1 exec/s 0
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#2 NEW cov 208 bits 0 units 2 exec/s 0 L: 64
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#3 NEW cov 217 bits 0 units 3 exec/s 0 L: 63
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#4 pulse cov 217 bits 0 units 3 exec/s 0
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* The ``Seed:`` line shows you the current random seed (you can change it with ``-seed=N`` flag).
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* 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).
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* The ``INITED`` line shows you that how many inputs will be fuzzed.
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* 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.
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* The ``pulse`` lines appear periodically to show the current status.
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Now, interrupt the fuzzer and run it again the same way. You will see::
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Seed: 1879995378
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#0 READ cov 0 bits 0 units 564 exec/s 0
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#1 pulse cov 502 bits 0 units 564 exec/s 0
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...
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#512 pulse cov 2933 bits 0 units 564 exec/s 512
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#564 INITED cov 2991 bits 0 units 344 exec/s 564
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#1024 pulse cov 2991 bits 0 units 344 exec/s 1024
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#1455 NEW cov 2995 bits 0 units 345 exec/s 1455 L: 49
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This time you were running the fuzzer with a non-empty input corpus (564 items).
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As the first step, the fuzzer minimized the set to produce 344 interesting items (the ``INITED`` line)
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You may run ``N`` independent fuzzer jobs in parallel on ``M`` CPUs::
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N=100; M=4; ./pcre_fuzzer ./CORPUS -jobs=$N -workers=$M
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This is useful when you already have an exhaustive test corpus.
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If you've just started fuzzing with no good corpus running independent
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jobs will create a corpus with too many duplicates.
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One way to avoid this and still use all of your CPUs is to use the flag ``-exit_on_first=1``
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which will cause the fuzzer to exit on the first new synthesised input::
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N=100; M=4; ./pcre_fuzzer ./CORPUS -jobs=$N -workers=$M -exit_on_first=1
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Heartbleed
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----------
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Remember Heartbleed_?
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As it was recently `shown <https://blog.hboeck.de/archives/868-How-Heartbleed-couldve-been-found.html>`_,
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fuzzing with AddressSanitizer can find Heartbleed. Indeed, here are the step-by-step instructions
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to find Heartbleed with LibFuzzer::
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wget https://www.openssl.org/source/openssl-1.0.1f.tar.gz
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tar xf openssl-1.0.1f.tar.gz
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COV_FLAGS="-fsanitize-coverage=edge,indirect-calls" # -fsanitize-coverage=8bit-counters
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(cd openssl-1.0.1f/ && ./config &&
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make -j 32 CC="clang -g -fsanitize=address $COV_FLAGS")
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# Get and build LibFuzzer
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svn co http://llvm.org/svn/llvm-project/llvm/trunk/lib/Fuzzer
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clang -c -g -O2 -std=c++11 Fuzzer/*.cpp -IFuzzer
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# Get examples of key/pem files.
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git clone https://github.com/hannob/selftls
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cp selftls/server* . -v
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cat << EOF > handshake-fuzz.cc
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#include <openssl/ssl.h>
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#include <openssl/err.h>
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#include <assert.h>
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SSL_CTX *sctx;
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int Init() {
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SSL_library_init();
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SSL_load_error_strings();
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ERR_load_BIO_strings();
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OpenSSL_add_all_algorithms();
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assert (sctx = SSL_CTX_new(TLSv1_method()));
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assert (SSL_CTX_use_certificate_file(sctx, "server.pem", SSL_FILETYPE_PEM));
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assert (SSL_CTX_use_PrivateKey_file(sctx, "server.key", SSL_FILETYPE_PEM));
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return 0;
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}
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extern "C" void LLVMFuzzerTestOneInput(unsigned char *Data, size_t Size) {
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static int unused = Init();
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SSL *server = SSL_new(sctx);
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BIO *sinbio = BIO_new(BIO_s_mem());
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BIO *soutbio = BIO_new(BIO_s_mem());
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SSL_set_bio(server, sinbio, soutbio);
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SSL_set_accept_state(server);
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BIO_write(sinbio, Data, Size);
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SSL_do_handshake(server);
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SSL_free(server);
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}
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EOF
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# Build the fuzzer.
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clang++ -g handshake-fuzz.cc -fsanitize=address \
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openssl-1.0.1f/libssl.a openssl-1.0.1f/libcrypto.a Fuzzer*.o
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# Run 20 independent fuzzer jobs.
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./a.out -jobs=20 -workers=20
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Voila::
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#1048576 pulse cov 3424 bits 0 units 9 exec/s 24385
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=================================================================
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==17488==ERROR: AddressSanitizer: heap-buffer-overflow on address 0x629000004748 at pc 0x00000048c979 bp 0x7fffe3e864f0 sp 0x7fffe3e85ca8
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READ of size 60731 at 0x629000004748 thread T0
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#0 0x48c978 in __asan_memcpy
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#1 0x4db504 in tls1_process_heartbeat openssl-1.0.1f/ssl/t1_lib.c:2586:3
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#2 0x580be3 in ssl3_read_bytes openssl-1.0.1f/ssl/s3_pkt.c:1092:4
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Advanced features
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=================
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Tokens
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------
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By default, the fuzzer is not aware of complexities of the input language
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and when fuzzing e.g. a C++ parser it will mostly stress the lexer.
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It is very hard for the fuzzer to come up with something like ``reinterpret_cast<int>``
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from a test corpus that doesn't have it.
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See a detailed discussion of this topic at
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http://lcamtuf.blogspot.com/2015/01/afl-fuzz-making-up-grammar-with.html.
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lib/Fuzzer implements a simple technique that allows to fuzz input languages with
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long tokens. All you need is to prepare a text file containing up to 253 tokens, one token per line,
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and pass it to the fuzzer as ``-tokens=TOKENS_FILE.txt``.
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Three implicit tokens are added: ``" "``, ``"\t"``, and ``"\n"``.
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The fuzzer itself will still be mutating a string of bytes
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but before passing this input to the target library it will replace every byte ``b`` with the ``b``-th token.
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If there are less than ``b`` tokens, a space will be added instead.
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AFL compatibility
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-----------------
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LibFuzzer can be used in parallel with AFL_ on the same test corpus.
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Both fuzzers expect the test corpus to reside in a directory, one file per input.
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You can run both fuzzers on the same corpus in parallel::
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./afl-fuzz -i testcase_dir -o findings_dir /path/to/program -r @@
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./llvm-fuzz testcase_dir findings_dir # Will write new tests to testcase_dir
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Periodically restart both fuzzers so that they can use each other's findings.
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How good is my fuzzer?
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----------------------
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Once you implement your target function ``LLVMFuzzerTestOneInput`` and fuzz it to death,
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you will want to know whether the function or the corpus can be improved further.
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One easy to use metric is, of course, code coverage.
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You can get the coverage for your corpus like this::
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ASAN_OPTIONS=coverage_pcs=1 ./fuzzer CORPUS_DIR -runs=0
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This will run all the tests in the CORPUS_DIR but will not generate any new tests
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and dump covered PCs to disk before exiting.
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Then you can subtract the set of covered PCs from the set of all instrumented PCs in the binary,
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see SanitizerCoverage_ for details.
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Fuzzing components of LLVM
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==========================
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clang-format-fuzzer
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-------------------
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The inputs are random pieces of C++-like text.
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Build (make sure to use fresh clang as the host compiler)::
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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
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ninja clang-format-fuzzer
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mkdir CORPUS_DIR
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./bin/clang-format-fuzzer CORPUS_DIR
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Optionally build other kinds of binaries (asan+Debug, msan, ubsan, etc).
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TODO: commit the pre-fuzzed corpus to svn (?).
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Tracking bug: https://llvm.org/bugs/show_bug.cgi?id=23052
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clang-fuzzer
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------------
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The default behavior is very similar to ``clang-format-fuzzer``.
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Clang can also be fuzzed with Tokens_ using ``-tokens=$LLVM/lib/Fuzzer/cxx_fuzzer_tokens.txt`` option.
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Tracking bug: https://llvm.org/bugs/show_bug.cgi?id=23057
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FAQ
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=========================
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Q. Why Fuzzer does not use any of the LLVM support?
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---------------------------------------------------
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There are two reasons.
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First, we want this library to be used outside of the LLVM w/o users having to
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build the rest of LLVM. This may sound unconvincing for many LLVM folks,
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but in practice the need for building the whole LLVM frightens many potential
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users -- and we want more users to use this code.
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Second, there is a subtle technical reason not to rely on the rest of LLVM, or
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any other large body of code (maybe not even STL). When coverage instrumentation
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is enabled, it will also instrument the LLVM support code which will blow up the
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coverage set of the process (since the fuzzer is in-process). In other words, by
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using more external dependencies we will slow down the fuzzer while the main
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reason for it to exist is extreme speed.
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Q. What about Windows then? The Fuzzer contains code that does not build on Windows.
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------------------------------------------------------------------------------------
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The sanitizer coverage support does not work on Windows either as of 01/2015.
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Once it's there, we'll need to re-implement OS-specific parts (I/O, signals).
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Q. When this Fuzzer is not a good solution for a problem?
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---------------------------------------------------------
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* If the test inputs are validated by the target library and the validator
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asserts/crashes on invalid inputs, the in-process fuzzer is not applicable
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(we could use fork() w/o exec, but it comes with extra overhead).
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* Bugs in the target library may accumulate w/o being detected. E.g. a memory
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corruption that goes undetected at first and then leads to a crash while
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testing another input. This is why it is highly recommended to run this
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in-process fuzzer with all sanitizers to detect most bugs on the spot.
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* It is harder to protect the in-process fuzzer from excessive memory
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consumption and infinite loops in the target library (still possible).
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* The target library should not have significant global state that is not
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reset between the runs.
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* Many interesting target libs are not designed in a way that supports
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the in-process fuzzer interface (e.g. require a file path instead of a
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byte array).
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* If a single test run takes a considerable fraction of a second (or
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more) the speed benefit from the in-process fuzzer is negligible.
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* If the target library runs persistent threads (that outlive
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execution of one test) the fuzzing results will be unreliable.
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Q. So, what exactly this Fuzzer is good for?
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--------------------------------------------
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This Fuzzer might be a good choice for testing libraries that have relatively
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small inputs, each input takes < 1ms to run, and the library code is not expected
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to crash on invalid inputs.
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Examples: regular expression matchers, text or binary format parsers.
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.. _pcre2: http://www.pcre.org/
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.. _AFL: http://lcamtuf.coredump.cx/afl/
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.. _SanitizerCoverage: http://clang.llvm.org/docs/SanitizerCoverage.html
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.. _Heartbleed: http://en.wikipedia.org/wiki/Heartbleed
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