def cleanse_testcase(runner, testcase_file_path, cleanse_to, cleanse_timeout, arguments, use_minijail): """Cleanse testcase.""" remove_fuzzing_arguments(arguments) # Write in-progress cleanse testcases to temp dir. if use_minijail: arguments.append(constants.TMP_ARTIFACT_PREFIX_ARGUMENT) else: cleanse_temp_dir = os.path.join(fuzzer_utils.get_temp_dir(), 'cleanse_temp') engine_common.recreate_directory(cleanse_temp_dir) arguments.append('%s%s/' % (constants.ARTIFACT_PREFIX_FLAG, cleanse_temp_dir)) # Call the fuzzer to cleanse. result = runner.cleanse_crash(testcase_file_path, cleanse_to, cleanse_timeout, additional_args=arguments) print( 'Running command:', get_printable_command(result.command, runner.executable_path, use_minijail)) print(result.output)
def mocked_fuzz(runner): """Mocked version of AflRunner.fuzz.""" fuzz_args = runner.generate_afl_args() runner._fuzz_args = fuzz_args # pylint: disable=protected-access engine_common.recreate_directory(runner.afl_output.output_directory) runner._fuzzer_stderr = '' # pylint: disable=protected-access # Create the queue directory within AFL's output directory. queue = runner.afl_output.queue engine_common.recreate_directory(queue) new_corpus_dir = os.path.join(DATA_DIRECTORY, 'merge_new_corpus') for filename in os.listdir(new_corpus_dir): src = os.path.join(new_corpus_dir, filename) dst = os.path.join(queue, filename) shutil.copy(src, dst) return new_process.ProcessResult( command=[], return_code=0, output='', time_executed=1)
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. if not corpus_directory: 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) fuzzing_strategies = [] # Select a generator to use for existing testcase mutations. generator = _select_generator() 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. corpus_directories = get_corpus_directories(corpus_directory, new_testcases_directory, fuzzer_path, fuzzing_strategies, 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]) max_len_argument = fuzzer_utils.extract_argument(arguments, constants.MAX_LEN_FLAG, remove=False) if not max_len_argument and do_random_max_length(): 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) if do_recommended_dictionary(): if add_recommended_dictionary(arguments, fuzzer_name, fuzzer_path): fuzzing_strategies.append(strategy.RECOMMENDED_DICTIONARY_STRATEGY) if do_value_profile(): arguments.append(constants.VALUE_PROFILE_ARGUMENT) fuzzing_strategies.append(strategy.VALUE_PROFILE_STRATEGY) if do_fork(): 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, num_fuzz_processes)) extra_env = {} if do_mutator_plugin(): if use_mutator_plugin(target_name, extra_env, minijail_chroot): fuzzing_strategies.append(strategy.MUTATOR_PLUGIN_STRATEGY) # 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. 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 create_corpus_directory(name): """Create a corpus directory with a give name in temp directory and return its full path.""" new_corpus_directory = os.path.join(fuzzer_utils.get_temp_dir(), name) engine_common.recreate_directory(new_corpus_directory) return new_corpus_directory
def _create_temp_corpus_dir(self, name): """Create temporary corpus directory.""" new_corpus_directory = os.path.join(fuzzer_utils.get_temp_dir(), name) engine_common.recreate_directory(new_corpus_directory) return new_corpus_directory
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 = environment.get_value('FUZZ_TARGET') if arguments and arguments[0] == target_name: # Pop legacy fuzz target argument. 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: 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) # If we don't have a corpus, then that means this is not a fuzzing run. if not corpus_directory: 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) # Set up scratch directory for writing new units. new_testcases_directory = create_corpus_directory('new') # 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( strategy_list=strategy.LIBFUZZER_STRATEGY_LIST, use_generator=True, engine_name='libFuzzer') strategy_info = pick_strategies( strategy_pool, fuzzer_path, corpus_directory, arguments, minijail_chroot=minijail_chroot) arguments.extend(strategy_info.arguments) # Timeout for fuzzer run. fuzz_timeout = get_fuzz_timeout(strategy_info.is_mutations_run) # 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, strategy_info.fuzzing_strategies, strategy_pool, minijail_chroot=minijail_chroot, allow_corpus_subset=not strategy_info.use_dataflow_tracing) corpus_directories.extend(strategy_info.additional_corpus_dirs) artifact_prefix = os.path.abspath(os.path.dirname(testcase_file_path)) # Execute the fuzzer binary with original arguments. fuzz_result = runner.fuzz( corpus_directories, fuzz_timeout=fuzz_timeout, artifact_prefix=artifact_prefix, additional_args=arguments, extra_env=strategy_info.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 = runner.get_testcase_path(log_lines) if crash_testcase_file_path: # Copy crash testcase contents into the main testcase path. shutil.move(crash_testcase_file_path, testcase_file_path) # Print the command output. 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(engine_common.get_log_header(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, strategy_info.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, 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. print(engine_common.format_fuzzing_strategies( strategy_info.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 _minimize_corpus_two_step(self, target_path, arguments, existing_corpus_dirs, new_corpus_dir, output_corpus_dir, reproducers_dir, max_time): """Optional (but recommended): run corpus minimization. Args: target_path: Path to the target. arguments: Additional arguments needed for corpus minimization. existing_corpus_dirs: Input corpora that existed before the fuzzing run. new_corpus_dir: Input corpus that was generated during the fuzzing run. Must have at least one new file. output_corpus_dir: Output directory to place minimized corpus. reproducers_dir: The directory to put reproducers in when crashes are found. max_time: Maximum allowed time for the minimization. Returns: A Result object. """ if not _is_multistep_merge_supported(target_path): # Fallback to the old single step merge. It does not support incremental # stats and provides only `edge_coverage` and `feature_coverage` stats. logs.log( 'Old version of libFuzzer is used. Using single step merge.') return self.minimize_corpus( target_path, arguments, existing_corpus_dirs + [new_corpus_dir], output_corpus_dir, reproducers_dir, max_time) # The dir where merge control file is located must persist for both merge # steps. The second step re-uses the MCF produced during the first step. merge_control_file_dir = self._create_temp_corpus_dir('mcf_tmp_dir') self._merge_control_file = os.path.join(merge_control_file_dir, 'MCF') # Two step merge process to obtain accurate stats for the new corpus units. # See https://reviews.llvm.org/D66107 for a more detailed description. merge_stats = {} # Step 1. Use only existing corpus and collect "initial" stats. result_1 = self.minimize_corpus(target_path, arguments, existing_corpus_dirs, output_corpus_dir, reproducers_dir, max_time) merge_stats['initial_edge_coverage'] = result_1.stats['edge_coverage'] merge_stats['initial_feature_coverage'] = result_1.stats[ 'feature_coverage'] # Clear the output dir as it does not have any new units at this point. engine_common.recreate_directory(output_corpus_dir) # Adjust the time limit for the time we spent on the first merge step. max_time -= result_1.time_executed if max_time <= 0: raise TimeoutError('Merging new testcases timed out\n' + result_1.logs) # Step 2. Process the new corpus units as well. result_2 = self.minimize_corpus( target_path, arguments, existing_corpus_dirs + [new_corpus_dir], output_corpus_dir, reproducers_dir, max_time) merge_stats['edge_coverage'] = result_2.stats['edge_coverage'] merge_stats['feature_coverage'] = result_2.stats['feature_coverage'] # Diff the stats to obtain accurate values for the new corpus units. merge_stats['new_edges'] = (merge_stats['edge_coverage'] - merge_stats['initial_edge_coverage']) merge_stats['new_features'] = (merge_stats['feature_coverage'] - merge_stats['initial_feature_coverage']) output = result_1.logs + '\n\n' + result_2.logs if (merge_stats['new_edges'] < 0 or merge_stats['new_features'] < 0): logs.log_error('Two step merge failed.', merge_stats=merge_stats, output=output) merge_stats['new_edges'] = 0 merge_stats['new_features'] = 0 self._merge_control_file = None # TODO(ochang): Get crashes found during merge. return engine.FuzzResult( output, result_2.command, [], merge_stats, result_1.time_executed + result_2.time_executed)
def create_new_if_needed(self): """Checks if any inputs are too large for AFL. If not then does nothing. Otherwise creates a temporary input directory and copies the non-oversized inputs. """ # TODO(metzman): Get rid of this approach where a new corpus is created. # Instead use an approach that modifies the input corpus permanently so that # it doesn't have to be fixed every time by AFL. # TODO(metzman): Copy testcases in subdirectories so AFL can use them, even # when there are no oversized files. corpus_file_paths = list_full_file_paths_recursive( self.input_directory) usable_files_and_sizes = [ (path, os.path.getsize(path)) for path in corpus_file_paths if os.path.getsize(path) < constants.MAX_FILE_BYTES ] num_files = len(usable_files_and_sizes) if self.strategies.use_corpus_subset: num_files = min(num_files, self.strategies.corpus_subset_size) self.strategies.use_corpus_subset = ( self.strategies.corpus_subset_size == num_files) if num_files == len(corpus_file_paths): # Nothing to do here: using full corpus and all files are appropriately # sized. return None # Save the original input directory. self.original_input_directory = self.input_directory # Make a new directory that we can modify. self.input_directory = os.path.join(fuzzer_utils.get_temp_dir(), 'afl_input_dir') engine_common.recreate_directory(self.input_directory) copied_size = 0 for src_path, src_size in usable_files_and_sizes: if not num_files: break num_files -= 1 copied_size += src_size if copied_size > self.MAX_COPIED_CORPUS_SIZE: break filename = os.path.basename(src_path) dst_path = os.path.join(self.input_directory, filename) # TODO(metzman): Ask Michal to allow skipping of oversized inputs # automatically. Just copy the small enough, files, we can't use soft # links because of AFL and we can't use hard links because they do not # work across devices. shutil.copy(src_path, dst_path) num_files = len(os.listdir(self.input_directory)) num_files_original = len(os.listdir(self.original_input_directory)) logs.log(( 'Temporary input directory contains %d files. Original contains %d.' % (num_files, num_files_original))) return self.input_directory
def __init__(self): self.output_directory = os.path.join(fuzzer_utils.get_temp_dir(), 'afl_output_dir') engine_common.recreate_directory(self.output_directory)
def main(argv): """Run afl as specified by argv.""" atexit.register(fuzzer_utils.cleanup) # Initialize variables. _, testcase_file_path, target_name = argv[:3] input_directory = environment.get_value('FUZZ_CORPUS_DIR') 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': 'afl', 'job_name': environment.get_value('JOB_NAME') }) 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()) config = AflConfig.from_target_path(fuzzer_path) runner = AflRunner(fuzzer_path, config, testcase_file_path, input_directory) # Add *SAN_OPTIONS overrides from .options file. engine_common.process_sanitizer_options_overrides(fuzzer_path) # If we don't have a corpus, then that means this is not a fuzzing run. if not input_directory: load_testcase_if_exists(runner, testcase_file_path) return # Make sure afl won't exit because of bad sanitizer options. set_additional_sanitizer_options_for_afl_fuzz() # Execute afl-fuzz on the fuzzing target. fuzz_result = runner.fuzz() # Print info for the fuzzer logs. command = fuzz_result.command print('Command: {0}\n' 'Bot: {1}\n' 'Time ran: {2}\n').format(engine_common.get_command_quoted(command), BOT_NAME, fuzz_result.time_executed) print fuzz_result.output runner.strategies.print_strategies() if fuzz_result.return_code: # If AFL returned a non-zero return code quit now without getting stats, # since they would be meaningless. print runner.fuzzer_stderr return stats_getter = stats.StatsGetter(runner.afl_output.stats_path, config.dict_path) try: new_units_generated, new_units_added, corpus_size = ( runner.libfuzzerize_corpus()) stats_getter.set_stats(fuzz_result.time_executed, new_units_generated, new_units_added, corpus_size, runner.strategies, runner.fuzzer_stderr, fuzz_result.output) engine_common.dump_big_query_data(stats_getter.stats, testcase_file_path, AFL_PREFIX, fuzzer_name, command) finally: print runner.fuzzer_stderr # Whenever new units are added to corpus, 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=stats_getter.stats)