This library is intended primarily for in-process coverage-guided fuzz testing (fuzzing) of other libraries. The typical workflow looks like this:
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.
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 Maximum 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 1200 Timeout in seconds (if positive). If one unit runs more than this number of seconds the process will abort.
max_total_time 0 If positive, indicates the maximal total time in seconds to run the fuzzer.
help 0 Print help.
merge 0 If 1, the 2-nd, 3-rd, etc corpora will be merged into the 1-st corpus. Only interesting units will be taken.
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.
sync_command 0 Execute an external command "<sync_command> <test_corpus>" to synchronize the test corpus.
sync_timeout 600 Minimum timeout between syncs.
use_traces 0 Experimental: use instruction traces
only_ascii 0 If 1, generate only ASCII (isprint+isspace) inputs.
test_single_input "" Use specified file content as test input. Test will be run only once. Useful for debugging a particular case.
artifact_prefix "" Write fuzzing artifacts (crash, timeout, or slow inputs) as $(artifact_prefix)file
exact_artifact_path "" Write the single artifact on failure (crash, timeout) as $(exact_artifact_path). This overrides -artifact_prefix and will not use checksum in the file name. Do not use the same path for several parallel processes.
For the full list of flags run the fuzzer binary with -help=1.
A simple function that does something interesting if it receives the input “HI!”:
cat << EOF >> test_fuzzer.cc
#include <stdint.h>
#include <stddef.h>
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
if (size > 0 && data[0] == 'H')
if (size > 1 && data[1] == 'I')
if (size > 2 && data[2] == '!')
__builtin_trap();
return 0;
}
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.
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 actual function that does something interesting with PCRE2.
cat << EOF > pcre_fuzzer.cc
#include <string.h>
#include <stdint.h>
#include "pcre2posix.h"
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
if (size < 1) return 0;
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;
return 0;
}
EOF
clang++ -g -fsanitize=address $COV_FLAGS -c -std=c++11 -I inst/include/ pcre_fuzzer.cc
# Link.
clang++ -g -fsanitize=address -Wl,--whole-archive inst/lib/*.a -Wl,-no-whole-archive Fuzzer*.o pcre_fuzzer.o -o pcre_fuzzer
This will give you a binary of the fuzzer, called pcre_fuzzer. Now, create a directory that will hold the test corpus:
mkdir -p CORPUS
For simple input languages like regular expressions this is all you need. For more complicated inputs populate the directory with some input samples. Now run the fuzzer with the corpus dir as the only parameter:
./pcre_fuzzer ./CORPUS
You will see output like this:
Seed: 1876794929
#0 READ cov 0 bits 0 units 1 exec/s 0
#1 pulse cov 3 bits 0 units 1 exec/s 0
#1 INITED cov 3 bits 0 units 1 exec/s 0
#2 pulse cov 208 bits 0 units 1 exec/s 0
#2 NEW cov 208 bits 0 units 2 exec/s 0 L: 64
#3 NEW cov 217 bits 0 units 3 exec/s 0 L: 63
#4 pulse cov 217 bits 0 units 3 exec/s 0
Now, interrupt the fuzzer and run it again the same way. You will see:
Seed: 1879995378
#0 READ cov 0 bits 0 units 564 exec/s 0
#1 pulse cov 502 bits 0 units 564 exec/s 0
...
#512 pulse cov 2933 bits 0 units 564 exec/s 512
#564 INITED cov 2991 bits 0 units 344 exec/s 564
#1024 pulse cov 2991 bits 0 units 344 exec/s 1024
#1455 NEW cov 2995 bits 0 units 345 exec/s 1455 L: 49
This time you were running the fuzzer with a non-empty input corpus (564 items). As the first step, the fuzzer minimized the set to produce 344 interesting items (the INITED line)
It is quite convenient to store test corpuses in git. As an example, here is a git repository with test inputs for the above PCRE2 fuzzer:
git clone https://github.com/kcc/fuzzing-with-sanitizers.git
./pcre_fuzzer ./fuzzing-with-sanitizers/pcre2/C1/
You may run N independent fuzzer jobs in parallel on M CPUs:
N=100; M=4; ./pcre_fuzzer ./CORPUS -jobs=$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.
Remember Heartbleed? As it was recently shown, 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>
#include <stdint.h>
#include <stddef.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" int LLVMFuzzerTestOneInput(const uint8_t *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);
return 0;
}
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
Note: a similar fuzzer is now a part of the boringssl source tree.
EXPERIMENTAL. LibFuzzer supports user-supplied dictionaries with input language keywords or other interesting byte sequences (e.g. multi-byte magic values). Use -dict=DICTIONARY_FILE. For some input languages using a dictionary may significantly improve the search speed. The dictionary syntax is similar to that used by AFL for its -x option:
# Lines starting with '#' and empty lines are ignored.
# Adds "blah" (w/o quotes) to the dictionary.
kw1="blah"
# Use \\ for backslash and \" for quotes.
kw2="\"ac\\dc\""
# Use \xAB for hex values
kw3="\xF7\xF8"
# the name of the keyword followed by '=' may be omitted:
"foo\x0Abar"
EXPERIMENTAL. With an additional compiler flag -fsanitize-coverage=trace-cmp (see SanitizerCoverageTraceDataFlow) and extra run-time flag -use_traces=1 the fuzzer will try to apply data-flow-guided fuzzing. That is, the fuzzer will record the inputs to comparison instructions, switch statements, and several libc functions (memcmp, strcmp, strncmp, etc). It will later use those recorded inputs during mutations.
This mode can be combined with DataFlowSanitizer to achieve better sensitivity.
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.
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.
LibFuzzer allows to use custom (user-supplied) mutators, see FuzzerInterface.h
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).
Tracking bug: https://llvm.org/bugs/show_bug.cgi?id=23052
The behavior is very similar to clang-format-fuzzer.
Tracking bug: https://llvm.org/bugs/show_bug.cgi?id=23057
Tracking bug: https://llvm.org/bugs/show_bug.cgi?id=24639
This tool fuzzes the MC layer. Currently it is only able to fuzz the disassembler but it is hoped that assembly, and round-trip verification will be added in future.
When run in dissassembly mode, the inputs are opcodes to be disassembled. The fuzzer will consume as many instructions as possible and will stop when it finds an invalid instruction or runs out of data.
Please note that the command line interface differs slightly from that of other fuzzers. The fuzzer arguments should follow --fuzzer-args and should have a single dash, while other arguments control the operation mode and target in a similar manner to llvm-mc and should have two dashes. For example:
llvm-mc-fuzzer --triple=aarch64-linux-gnu --disassemble --fuzzer-args -max_len=4 -jobs=10
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 .
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/llvm-as-fuzzer fuzzing-with-sanitizers/llvm/llvm-as/C1 -only_ascii=1
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.
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).
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.