def test_strategy_pool_deterministic(self):
"""Tests whether a proper strategy pool is returned by the multi armed
bandit selection implementation.
Based on deterministic strategy selection. Mutator plugin is patched to
be included in our strategy pool."""
strategy_pool = strategy_selection.generate_weighted_strategy_pool()
self.assertTrue(
strategy_pool.do_strategy(
strategy.CORPUS_MUTATION_ML_RNN_STRATEGY))
self.assertTrue(
strategy_pool.do_strategy(strategy.RANDOM_MAX_LENGTH_STRATEGY))
self.assertTrue(
strategy_pool.do_strategy(strategy.VALUE_PROFILE_STRATEGY))
self.assertTrue(
strategy_pool.do_strategy(
strategy.RECOMMENDED_DICTIONARY_STRATEGY))
self.assertFalse(
strategy_pool.do_strategy(
strategy.CORPUS_MUTATION_RADAMSA_STRATEGY))
self.assertFalse(
strategy_pool.do_strategy(strategy.CORPUS_SUBSET_STRATEGY))
self.assertFalse(strategy_pool.do_strategy(strategy.FORK_STRATEGY))
self.assertTrue(
strategy_pool.do_strategy(strategy.MUTATOR_PLUGIN_STRATEGY))
def test_multi_armed_bandit_strategy_pool(self):
"""Ensures a call to the multi armed bandit strategy selection function
doesn't yield an exception through any of the experimental paths."""
environment.set_value('STRATEGY_SELECTION_METHOD', 'default')
strategy_selection.generate_weighted_strategy_pool()
environment.set_value('STRATEGY_SELECTION_METHOD',
'multi_armed_bandit_medium')
strategy_selection.generate_weighted_strategy_pool()
environment.set_value('STRATEGY_SELECTION_METHOD',
'multi_armed_bandit_high')
strategy_selection.generate_weighted_strategy_pool()
environment.set_value('STRATEGY_SELECTION_METHOD',
'multi_armed_bandit_low')
strategy_selection.generate_weighted_strategy_pool()
def main(argv):
"""Run libFuzzer as specified by argv."""
atexit.register(fuzzer_utils.cleanup)
# Initialize variables.
arguments = argv[1:]
testcase_file_path = arguments.pop(0)
target_name = arguments.pop(0)
fuzzer_name = data_types.fuzz_target_project_qualified_name(
utils.current_project(), target_name)
# Initialize log handler.
logs.configure(
'run_fuzzer', {
'fuzzer': fuzzer_name,
'engine': 'libFuzzer',
'job_name': environment.get_value('JOB_NAME')
})
profiler.start_if_needed('libfuzzer_launcher')
# Make sure that the fuzzer binary exists.
build_directory = environment.get_value('BUILD_DIR')
fuzzer_path = engine_common.find_fuzzer_path(build_directory, target_name)
if not fuzzer_path:
# This is an expected case when doing regression testing with old builds
# that do not have that fuzz target. It can also happen when a host sends a
# message to an untrusted worker that just restarted and lost information on
# build directory.
logs.log_warn('Could not find fuzz target %s.' % target_name)
return
# Install signal handler.
signal.signal(signal.SIGTERM, engine_common.signal_term_handler)
# Set up temp dir.
engine_common.recreate_directory(fuzzer_utils.get_temp_dir())
# Setup minijail if needed.
use_minijail = environment.get_value('USE_MINIJAIL')
runner = libfuzzer.get_runner(fuzzer_path,
temp_dir=fuzzer_utils.get_temp_dir())
if use_minijail:
minijail_chroot = runner.chroot
else:
minijail_chroot = None
# Get corpus directory.
corpus_directory = environment.get_value('FUZZ_CORPUS_DIR')
# Add common arguments which are necessary to be used for every run.
arguments = expand_with_common_arguments(arguments)
# Add sanitizer options to environment that were specified in the .options
# file and options that this script requires.
set_sanitizer_options(fuzzer_path)
# Minimize test argument.
minimize_to = fuzzer_utils.extract_argument(arguments,
MINIMIZE_TO_ARGUMENT)
minimize_timeout = fuzzer_utils.extract_argument(
arguments, MINIMIZE_TIMEOUT_ARGUMENT)
if minimize_to and minimize_timeout:
minimize_testcase(runner, testcase_file_path, minimize_to,
int(minimize_timeout), arguments, use_minijail)
return
# Cleanse argument.
cleanse_to = fuzzer_utils.extract_argument(arguments, CLEANSE_TO_ARGUMENT)
cleanse_timeout = fuzzer_utils.extract_argument(arguments,
CLEANSE_TIMEOUT_ARGUMENT)
if cleanse_to and cleanse_timeout:
cleanse_testcase(runner, testcase_file_path, cleanse_to,
int(cleanse_timeout), arguments, use_minijail)
return
# If we don't have a corpus, then that means this is not a fuzzing run.
# TODO(flowerhack): Implement this to properly load past testcases.
if not corpus_directory and environment.platform() != 'FUCHSIA':
load_testcase_if_exists(runner, testcase_file_path, fuzzer_name,
use_minijail, arguments)
return
# We don't have a crash testcase, fuzz.
# Check dict argument to make sure that it's valid.
dict_argument = fuzzer_utils.extract_argument(arguments,
constants.DICT_FLAG,
remove=False)
if dict_argument and not os.path.exists(dict_argument):
logs.log_error('Invalid dict %s for %s.' %
(dict_argument, fuzzer_name))
fuzzer_utils.extract_argument(arguments, constants.DICT_FLAG)
# If there's no dict argument, check for %target_binary_name%.dict file.
if (not fuzzer_utils.extract_argument(
arguments, constants.DICT_FLAG, remove=False)):
default_dict_path = dictionary_manager.get_default_dictionary_path(
fuzzer_path)
if os.path.exists(default_dict_path):
arguments.append(constants.DICT_FLAG + default_dict_path)
# Strategy pool is the list of strategies that we attempt to enable, whereas
# fuzzing strategies is the list of strategies that are enabled. (e.g. if
# mutator is selected in the pool, but not available for a given target, it
# would not be added to fuzzing strategies.)
strategy_pool = strategy_selection.generate_weighted_strategy_pool()
fuzzing_strategies = []
# Select a generator to use for existing testcase mutations.
generator = _select_generator(strategy_pool, fuzzer_path)
is_mutations_run = generator != Generator.NONE
# Timeout for fuzzer run.
fuzz_timeout = get_fuzz_timeout(is_mutations_run)
# Set up scratch directory for writing new units.
new_testcases_directory = create_corpus_directory('new')
# Get list of corpus directories.
# TODO(flowerhack): Implement this to handle corpus sync'ing.
if environment.platform() == 'FUCHSIA':
corpus_directories = []
else:
corpus_directories = get_corpus_directories(
corpus_directory, new_testcases_directory, fuzzer_path,
fuzzing_strategies, strategy_pool, minijail_chroot)
# Bind corpus directories in minijail.
if use_minijail:
artifact_prefix = constants.ARTIFACT_PREFIX_FLAG + '/'
else:
artifact_prefix = '%s%s/' % (constants.ARTIFACT_PREFIX_FLAG,
os.path.abspath(
os.path.dirname(testcase_file_path)))
# Generate new testcase mutations using radamsa, etc.
if is_mutations_run:
new_testcase_mutations_directory = generate_new_testcase_mutations(
corpus_directory, fuzzer_name, generator, fuzzing_strategies)
corpus_directories.append(new_testcase_mutations_directory)
if use_minijail:
bind_corpus_dirs(minijail_chroot,
[new_testcase_mutations_directory])
if strategy_pool.do_strategy(strategy.RANDOM_MAX_LENGTH_STRATEGY):
max_len_argument = fuzzer_utils.extract_argument(
arguments, constants.MAX_LEN_FLAG, remove=False)
if not max_len_argument:
max_length = random.SystemRandom().randint(
1, MAX_VALUE_FOR_MAX_LENGTH)
arguments.append('%s%d' % (constants.MAX_LEN_FLAG, max_length))
fuzzing_strategies.append(strategy.RANDOM_MAX_LENGTH_STRATEGY.name)
if (strategy_pool.do_strategy(strategy.RECOMMENDED_DICTIONARY_STRATEGY) and
add_recommended_dictionary(arguments, fuzzer_name, fuzzer_path)):
fuzzing_strategies.append(
strategy.RECOMMENDED_DICTIONARY_STRATEGY.name)
if strategy_pool.do_strategy(strategy.VALUE_PROFILE_STRATEGY):
arguments.append(constants.VALUE_PROFILE_ARGUMENT)
fuzzing_strategies.append(strategy.VALUE_PROFILE_STRATEGY.name)
if strategy_pool.do_strategy(strategy.FORK_STRATEGY):
max_fuzz_threads = environment.get_value('MAX_FUZZ_THREADS', 1)
num_fuzz_processes = max(
1,
multiprocessing.cpu_count() // max_fuzz_threads)
arguments.append('%s%d' % (constants.FORK_FLAG, num_fuzz_processes))
fuzzing_strategies.append(
'%s_%d' % (strategy.FORK_STRATEGY.name, num_fuzz_processes))
extra_env = {}
if (strategy_pool.do_strategy(strategy.MUTATOR_PLUGIN_STRATEGY)
and use_mutator_plugin(target_name, extra_env, minijail_chroot)):
fuzzing_strategies.append(strategy.MUTATOR_PLUGIN_STRATEGY.name)
# Execute the fuzzer binary with original arguments.
fuzz_result = runner.fuzz(corpus_directories,
fuzz_timeout=fuzz_timeout,
additional_args=arguments + [artifact_prefix],
extra_env=extra_env)
if (not use_minijail
and fuzz_result.return_code == constants.LIBFUZZER_ERROR_EXITCODE):
# Minijail returns 1 if the exit code is nonzero.
# Otherwise: we can assume that a return code of 1 means that libFuzzer
# itself ran into an error.
logs.log_error(ENGINE_ERROR_MESSAGE, engine_output=fuzz_result.output)
log_lines = fuzz_result.output.splitlines()
# Output can be large, so save some memory by removing reference to the
# original output which is no longer needed.
fuzz_result.output = None
# Check if we crashed, and get the crash testcase path.
crash_testcase_file_path = None
for line in log_lines:
match = re.match(CRASH_TESTCASE_REGEX, line)
if match:
crash_testcase_file_path = match.group(1)
break
if crash_testcase_file_path:
# Write the new testcase.
if use_minijail:
# Convert chroot relative path to host path. Remove the leading '/' before
# joining.
crash_testcase_file_path = os.path.join(
minijail_chroot.directory, crash_testcase_file_path[1:])
# Copy crash testcase contents into the main testcase path.
shutil.move(crash_testcase_file_path, testcase_file_path)
# Print the command output.
log_header_format = ('Command: %s\n' 'Bot: %s\n' 'Time ran: %f\n')
bot_name = environment.get_value('BOT_NAME', '')
command = fuzz_result.command
if use_minijail:
# Remove minijail prefix.
command = engine_common.strip_minijail_command(command, fuzzer_path)
print(log_header_format % (engine_common.get_command_quoted(command),
bot_name, fuzz_result.time_executed))
# Parse stats information based on libFuzzer output.
parsed_stats = parse_log_stats(log_lines)
# Extend parsed stats by additional performance features.
parsed_stats.update(
stats.parse_performance_features(log_lines, fuzzing_strategies,
arguments))
# Set some initial stat overrides.
timeout_limit = fuzzer_utils.extract_argument(arguments,
constants.TIMEOUT_FLAG,
remove=False)
expected_duration = runner.get_max_total_time(fuzz_timeout)
actual_duration = int(fuzz_result.time_executed)
fuzzing_time_percent = 100 * actual_duration / float(expected_duration)
stat_overrides = {
'timeout_limit': int(timeout_limit),
'expected_duration': expected_duration,
'actual_duration': actual_duration,
'fuzzing_time_percent': fuzzing_time_percent,
}
# Remove fuzzing arguments before merge and dictionary analysis step.
remove_fuzzing_arguments(arguments)
# Make a decision on whether merge step is needed at all. If there are no
# new units added by libFuzzer run, then no need to do merge at all.
new_units_added = shell.get_directory_file_count(new_testcases_directory)
merge_error = None
if new_units_added:
# Merge the new units with the initial corpus.
if corpus_directory not in corpus_directories:
corpus_directories.append(corpus_directory)
# If this times out, it's possible that we will miss some units. However, if
# we're taking >10 minutes to load/merge the corpus something is going very
# wrong and we probably don't want to make things worse by adding units
# anyway.
merge_tmp_dir = None
if not use_minijail:
merge_tmp_dir = os.path.join(fuzzer_utils.get_temp_dir(),
'merge_workdir')
engine_common.recreate_directory(merge_tmp_dir)
old_corpus_len = shell.get_directory_file_count(corpus_directory)
merge_directory = create_merge_directory()
corpus_directories.insert(0, merge_directory)
if use_minijail:
bind_corpus_dirs(minijail_chroot, [merge_directory])
merge_result = runner.merge(
corpus_directories,
merge_timeout=engine_common.get_merge_timeout(
DEFAULT_MERGE_TIMEOUT),
tmp_dir=merge_tmp_dir,
additional_args=arguments)
move_mergeable_units(merge_directory, corpus_directory)
new_corpus_len = shell.get_directory_file_count(corpus_directory)
new_units_added = 0
merge_error = None
if merge_result.timed_out:
merge_error = 'Merging new testcases timed out:'
elif merge_result.return_code != 0:
merge_error = 'Merging new testcases failed:'
else:
new_units_added = new_corpus_len - old_corpus_len
stat_overrides['new_units_added'] = new_units_added
if merge_result.output:
stat_overrides.update(
stats.parse_stats_from_merge_log(
merge_result.output.splitlines()))
else:
stat_overrides['new_units_added'] = 0
logs.log('Skipped corpus merge since no new units added by fuzzing.')
# Get corpus size after merge. This removes the duplicate units that were
# created during this fuzzing session.
# TODO(flowerhack): Remove this workaround once we can handle corpus sync.
if environment.platform() != 'FUCHSIA':
stat_overrides['corpus_size'] = shell.get_directory_file_count(
corpus_directory)
# Delete all corpus directories except for the main one. These were temporary
# directories to store new testcase mutations and have already been merged to
# main corpus directory.
if corpus_directory in corpus_directories:
corpus_directories.remove(corpus_directory)
for directory in corpus_directories:
shutil.rmtree(directory, ignore_errors=True)
if use_minijail:
unbind_corpus_dirs(minijail_chroot, corpus_directories)
# Apply overridden stats to the parsed stats prior to dumping.
parsed_stats.update(stat_overrides)
# Dump stats data for further uploading to BigQuery.
engine_common.dump_big_query_data(parsed_stats, testcase_file_path,
LIBFUZZER_PREFIX, fuzzer_name, command)
# Add custom crash state based on fuzzer name (if needed).
add_custom_crash_state_if_needed(fuzzer_name, log_lines, parsed_stats)
for line in log_lines:
print(line)
# Add fuzzing strategies used.
engine_common.print_fuzzing_strategies(fuzzing_strategies)
# Add merge error (if any).
if merge_error:
print(data_types.CRASH_STACKTRACE_END_MARKER)
print(merge_error)
print(
'Command:',
get_printable_command(merge_result.command, fuzzer_path,
use_minijail))
print(merge_result.output)
analyze_and_update_recommended_dictionary(runner, fuzzer_name, log_lines,
corpus_directory, arguments)
# Close minijail chroot.
if use_minijail:
minijail_chroot.close()
# Record the stats to make them easily searchable in stackdriver.
if new_units_added:
logs.log('New units added to corpus: %d.' % new_units_added,
stats=parsed_stats)
else:
logs.log('No new units found.', stats=parsed_stats)
def test_multi_armed_bandit_strategy_pool(self):
"""Ensures a call to the multi armed bandit strategy selection function
doesn't yield an exception."""
strategy_selection.generate_weighted_strategy_pool()