AFLplusplus/afl-cmin.py

761 lines
22 KiB
Python
Executable File

#!/usr/bin/env python3
# Copyright 2016-2025 Google Inc.
# Copyright 2025 AFLplusplus Project. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import argparse
import array
import base64
import collections
import glob
import hashlib
import itertools
import logging
import multiprocessing
import os
import shutil
import subprocess
import sys
# https://more-itertools.readthedocs.io/en/stable/_modules/more_itertools/recipes.html#batched
from sys import hexversion
def _batched(iterable, n, *, strict=False):
"""Batch data into tuples of length *n*. If the number of items in
*iterable* is not divisible by *n*:
* The last batch will be shorter if *strict* is ``False``.
* :exc:`ValueError` will be raised if *strict* is ``True``.
>>> list(batched('ABCDEFG', 3))
[('A', 'B', 'C'), ('D', 'E', 'F'), ('G',)]
On Python 3.13 and above, this is an alias for :func:`itertools.batched`.
"""
if n < 1:
raise ValueError('n must be at least one')
iterator = iter(iterable)
while batch := tuple(itertools.islice(iterator, n)):
if strict and len(batch) != n:
raise ValueError('batched(): incomplete batch')
yield batch
if hexversion >= 0x30D00A2: # pragma: no cover
from itertools import batched as itertools_batched
def batched(iterable, n, *, strict=False):
return itertools_batched(iterable, n, strict=strict)
else:
batched = _batched
batched.__doc__ = _batched.__doc__
try:
from tqdm import tqdm
except ImportError:
print('Hint: install python module "tqdm" to show progress bar')
class tqdm:
def __init__(self, data=None, *args, **argd):
self.data = data
def __iter__(self):
yield from self.data
def __enter__(self):
return self
def __exit__(self, exc_type, exc_value, traceback):
pass
def update(self, *args):
pass
parser = argparse.ArgumentParser()
cpu_count = multiprocessing.cpu_count()
group = parser.add_argument_group("Required parameters")
group.add_argument(
"-i",
dest="input",
action="append",
metavar="dir",
required=True,
help="input directory with the starting corpus",
)
group.add_argument(
"-o",
dest="output",
metavar="dir",
required=True,
help="output directory for minimized files",
)
group = parser.add_argument_group("Execution control settings")
group.add_argument(
"-f",
dest="stdin_file",
metavar="file",
help="location read by the fuzzed program (stdin)",
)
group.add_argument(
"-m",
dest="memory_limit",
default="none",
metavar="megs",
type=lambda x: x if x == "none" else int(x),
help="memory limit for child process (default: %(default)s)",
)
group.add_argument(
"-t",
dest="time_limit",
default=5000,
metavar="msec",
type=lambda x: x if x == "none" else int(x),
help="timeout for each run (default: %(default)s)",
)
group.add_argument(
"-O",
dest="frida_mode",
action="store_true",
default=False,
help="use binary-only instrumentation (FRIDA mode)",
)
group.add_argument(
"-Q",
dest="qemu_mode",
action="store_true",
default=False,
help="use binary-only instrumentation (QEMU mode)",
)
group.add_argument(
"-U",
dest="unicorn_mode",
action="store_true",
default=False,
help="use unicorn-based instrumentation (Unicorn mode)",
)
group.add_argument(
"-X", dest="nyx_mode", action="store_true", default=False, help="use Nyx mode"
)
group = parser.add_argument_group("Minimization settings")
group.add_argument(
"--crash-dir",
dest="crash_dir",
metavar="dir",
default=None,
help="move crashes to a separate dir, always deduplicated",
)
group.add_argument(
"-A",
dest="allow_any",
action="store_true",
help="allow crashes and timeouts (not recommended)",
)
group.add_argument(
"-C",
dest="crash_only",
action="store_true",
help="keep crashing inputs, reject everything else",
)
group.add_argument(
"-e",
dest="edge_mode",
action="store_true",
default=False,
help="solve for edge coverage only, ignore hit counts",
)
group = parser.add_argument_group("Misc")
group.add_argument(
"-T",
dest="workers",
type=lambda x: cpu_count if x == "all" else int(x),
default=1,
help="number of concurrent worker (default: %(default)d)",
)
group.add_argument(
"--as_queue",
action="store_true",
help='output file name like "id:000000,hash:value"',
)
group.add_argument(
"--no-dedup", action="store_true", help="skip deduplication step for corpus files"
)
group.add_argument("--debug", action="store_true")
parser.add_argument("exe", metavar="/path/to/target_app")
parser.add_argument("args", nargs="*")
args = parser.parse_args()
logger = None
afl_showmap_bin = None
tuple_index_type_code = "I"
file_index_type_code = None
def init():
global logger
log_level = logging.DEBUG if args.debug else logging.INFO
logging.basicConfig(
level=log_level, format="%(asctime)s - %(levelname)s - %(message)s"
)
logger = logging.getLogger(__name__)
if args.stdin_file and args.workers > 1:
logger.error("-f is only supported with one worker (-T 1)")
sys.exit(1)
if args.memory_limit != "none" and args.memory_limit < 5:
logger.error("dangerously low memory limit")
sys.exit(1)
if args.time_limit != "none" and args.time_limit < 10:
logger.error("dangerously low timeout")
sys.exit(1)
if not os.path.isfile(args.exe):
logger.error('binary "%s" not found or not regular file', args.exe)
sys.exit(1)
if not os.environ.get("AFL_SKIP_BIN_CHECK") and not any(
[args.qemu_mode, args.frida_mode, args.unicorn_mode, args.nyx_mode]
):
if b"__AFL_SHM_ID" not in open(args.exe, "rb").read():
logger.error("binary '%s' doesn't appear to be instrumented", args.exe)
sys.exit(1)
for dn in args.input:
if not os.path.isdir(dn) and not glob.glob(dn):
logger.error('directory "%s" not found', dn)
sys.exit(1)
global afl_showmap_bin
searches = [
None,
os.path.dirname(__file__),
os.getcwd(),
]
if os.environ.get("AFL_PATH"):
searches.append(os.environ["AFL_PATH"])
for search in searches:
afl_showmap_bin = shutil.which("afl-showmap", path=search)
if afl_showmap_bin:
break
if not afl_showmap_bin:
logger.fatal("cannot find afl-showmap, please set AFL_PATH")
sys.exit(1)
trace_dir = os.path.join(args.output, ".traces")
shutil.rmtree(trace_dir, ignore_errors=True)
try:
os.rmdir(args.output)
except OSError:
pass
if os.path.exists(args.output):
logger.error(
'directory "%s" exists and is not empty - delete it first', args.output
)
sys.exit(1)
if args.crash_dir and not os.path.exists(args.crash_dir):
os.makedirs(args.crash_dir)
os.makedirs(trace_dir)
logger.info("use %d workers (-T)", args.workers)
def detect_type_code(size):
for type_code in ["B", "H", "I", "L", "Q"]:
if 256 ** array.array(type_code).itemsize > size:
return type_code
def afl_showmap(input_path=None, batch=None, afl_map_size=None, first=False):
assert input_path or batch
# yapf: disable
cmd = [
afl_showmap_bin,
'-m', str(args.memory_limit),
'-t', str(args.time_limit),
'-Z', # cmin mode
]
# yapf: enable
found_atat = False
for arg in args.args:
if "@@" in arg:
found_atat = True
if args.stdin_file:
assert args.workers == 1
input_from_file = True
stdin_file = args.stdin_file
cmd += ["-H", stdin_file]
elif found_atat:
input_from_file = True
stdin_file = os.path.join(args.output, f".input.{os.getpid()}")
cmd += ["-H", stdin_file]
else:
input_from_file = False
if batch:
input_from_file = True
filelist = os.path.join(args.output, f".filelist.{os.getpid()}")
with open(filelist, "w") as f:
for _, path in batch:
f.write(path + "\n")
cmd += ["-I", filelist]
output_path = os.path.join(args.output, f".showmap.{os.getpid()}")
cmd += ["-o", output_path]
else:
if input_from_file:
shutil.copy(input_path, stdin_file)
cmd += ["-o", "-"]
if args.frida_mode:
cmd += ["-O"]
if args.qemu_mode:
cmd += ["-Q"]
if args.unicorn_mode:
cmd += ["-U"]
if args.nyx_mode:
cmd += ["-X"]
if args.edge_mode:
cmd += ["-e"]
cmd += ["--", args.exe] + args.args
env = os.environ.copy()
env["AFL_QUIET"] = "1"
env["ASAN_OPTIONS"] = "detect_leaks=0"
if first:
logger.debug("run command line: %s", subprocess.list2cmdline(cmd))
env["AFL_CMIN_ALLOW_ANY"] = "1"
if afl_map_size:
env["AFL_MAP_SIZE"] = str(afl_map_size)
if args.crash_only:
env["AFL_CMIN_CRASHES_ONLY"] = "1"
if args.allow_any:
env["AFL_CMIN_ALLOW_ANY"] = "1"
if input_from_file:
p = subprocess.Popen(cmd, stdout=subprocess.PIPE, env=env, bufsize=1048576)
else:
p = subprocess.Popen(
cmd,
stdin=open(input_path, "rb"),
stdout=subprocess.PIPE,
env=env,
bufsize=1048576,
)
out = p.stdout.read()
p.wait()
if batch:
result = []
for idx, input_path in batch:
basename = os.path.basename(input_path)
values = []
try:
trace_file = os.path.join(output_path, basename)
with open(trace_file, "r") as f:
values = list(map(int, f))
crashed = len(values) == 0
os.unlink(trace_file)
except FileNotFoundError:
a = None
crashed = True
values = [(t // 1000) * 9 + t % 1000 for t in values]
a = array.array(tuple_index_type_code, values)
result.append((idx, a, crashed))
os.unlink(filelist)
os.rmdir(output_path)
return result
else:
values = []
for line in out.split():
if not line.isdigit():
continue
values.append(int(line))
values = [(t // 1000) * 9 + t % 1000 for t in values]
a = array.array(tuple_index_type_code, values)
crashed = p.returncode in [2, 3]
if input_from_file and stdin_file != args.stdin_file:
os.unlink(stdin_file)
return a, crashed
class JobDispatcher(multiprocessing.Process):
def __init__(self, job_queue, jobs):
super().__init__()
self.job_queue = job_queue
self.jobs = jobs
def run(self):
for job in self.jobs:
self.job_queue.put(job)
self.job_queue.close()
class Worker(multiprocessing.Process):
def __init__(self, idx, afl_map_size, q_in, p_out, r_out):
super().__init__()
self.idx = idx
self.afl_map_size = afl_map_size
self.q_in = q_in
self.p_out = p_out
self.r_out = r_out
def run(self):
map_size = self.afl_map_size or 65536
max_tuple = map_size * 9
max_file_index = 256 ** array.array(file_index_type_code).itemsize - 1
m = array.array(file_index_type_code, [max_file_index] * max_tuple)
counter = collections.Counter()
crashes = []
pack_name = os.path.join(args.output, ".traces", f"{self.idx}.pack")
pack_pos = 0
with open(pack_name, "wb") as trace_pack:
while True:
batch = self.q_in.get()
if batch is None:
break
for idx, r, crash in afl_showmap(
batch=batch, afl_map_size=self.afl_map_size
):
counter.update(r)
used = False
if crash:
crashes.append(idx)
# If we aren't saving crashes to a separate dir, handle them
# the same as other inputs. However, unless AFL_CMIN_ALLOW_ANY=1,
# afl_showmap will not return any coverage for crashes so they will
# never be retained.
if not crash or not args.crash_dir:
for t in r:
if idx < m[t]:
m[t] = idx
used = True
if used:
tuple_count = len(r)
r.tofile(trace_pack)
self.p_out.put((idx, self.idx, pack_pos, tuple_count))
pack_pos += tuple_count * r.itemsize
else:
self.p_out.put(None)
self.r_out.put((self.idx, m, counter, crashes))
class CombineTraceWorker(multiprocessing.Process):
def __init__(self, pack_name, jobs, r_out):
super().__init__()
self.pack_name = pack_name
self.jobs = jobs
self.r_out = r_out
def run(self):
already_have = set()
with open(self.pack_name, "rb") as f:
for pos, tuple_count in self.jobs:
f.seek(pos)
result = array.array(tuple_index_type_code)
result.fromfile(f, tuple_count)
already_have.update(result)
self.r_out.put(already_have)
def hash_file(path):
m = hashlib.sha1()
with open(path, "rb") as f:
m.update(f.read())
return m.digest()
def dedup(files):
with multiprocessing.Pool(args.workers) as pool:
seen_hash = set()
result = []
hash_list = []
# use large chunksize to reduce multiprocessing overhead
chunksize = max(1, min(256, len(files) // args.workers))
for i, h in enumerate(
tqdm(
pool.imap(hash_file, files, chunksize),
desc="dedup",
total=len(files),
ncols=0,
leave=(len(files) > 100000),
)
):
if h in seen_hash:
continue
seen_hash.add(h)
result.append(files[i])
hash_list.append(h)
return result, hash_list
def is_afl_dir(dirnames, filenames):
return (
"queue" in dirnames
and "hangs" in dirnames
and "crashes" in dirnames
and "fuzzer_setup" in filenames
)
def collect_files(input_paths):
paths = []
for s in input_paths:
paths += glob.glob(s)
files = []
with tqdm(desc="search", unit=" files", ncols=0) as pbar:
for path in paths:
for root, dirnames, filenames in os.walk(path, followlinks=True):
for dirname in dirnames:
if dirname.startswith("."):
dirnames.remove(dirname)
if not args.crash_only and is_afl_dir(dirnames, filenames):
continue
for filename in filenames:
if filename.startswith("."):
continue
pbar.update(1)
files.append(os.path.join(root, filename))
return files
def main():
init()
files = collect_files(args.input)
if len(files) == 0:
logger.error("no inputs in the target directory - nothing to be done")
sys.exit(1)
logger.info("Found %d input files in %d directories", len(files), len(args.input))
if not args.no_dedup:
files, hash_list = dedup(files)
logger.info("Remain %d files after dedup", len(files))
else:
logger.info("Skipping file deduplication.")
global file_index_type_code
file_index_type_code = detect_type_code(len(files))
logger.info("Sorting files.")
with multiprocessing.Pool(args.workers) as pool:
chunksize = max(1, min(512, len(files) // args.workers))
size_list = list(pool.map(os.path.getsize, files, chunksize))
idxes = sorted(range(len(files)), key=lambda x: size_list[x])
files = [files[idx] for idx in idxes]
hash_list = [hash_list[idx] for idx in idxes]
afl_map_size = None
if b"AFL_DUMP_MAP_SIZE" in open(args.exe, "rb").read():
output = subprocess.run(
[args.exe], capture_output=True, env={"AFL_DUMP_MAP_SIZE": "1", "ASAN_OPTIONS": "detect_leaks=0"}
).stdout
afl_map_size = int(output)
logger.info("Setting AFL_MAP_SIZE=%d", afl_map_size)
global tuple_index_type_code
tuple_index_type_code = detect_type_code(afl_map_size * 9)
logger.info("Testing the target binary")
tuples, _ = afl_showmap(files[0], afl_map_size=afl_map_size, first=True)
if tuples:
logger.info("ok, %d tuples recorded", len(tuples))
else:
logger.error("no instrumentation output detected")
sys.exit(1)
job_queue = multiprocessing.Queue()
progress_queue = multiprocessing.Queue()
result_queue = multiprocessing.Queue()
workers = []
for i in range(args.workers):
p = Worker(i, afl_map_size, job_queue, progress_queue, result_queue)
p.start()
workers.append(p)
chunk = max(1, min(128, len(files) // args.workers))
jobs = list(batched(enumerate(files), chunk))
jobs += [None] * args.workers # sentinel
dispatcher = JobDispatcher(job_queue, jobs)
dispatcher.start()
logger.info("Processing traces")
effective = 0
trace_info = {}
for _ in tqdm(files, ncols=0, smoothing=0.01):
r = progress_queue.get()
if r is not None:
idx, worker_idx, pos, tuple_count = r
trace_info[idx] = worker_idx, pos, tuple_count
effective += 1
dispatcher.join()
logger.info("Obtaining trace results")
ms = []
crashes = []
counter = collections.Counter()
for _ in tqdm(range(args.workers), ncols=0):
idx, m, c, crs = result_queue.get()
ms.append(m)
counter.update(c)
crashes.extend(crs)
workers[idx].join()
best_idxes = list(map(min, zip(*ms)))
if not args.crash_dir:
logger.info(
"Found %d unique tuples across %d files (%d effective)",
len(counter),
len(files),
effective,
)
else:
logger.info(
"Found %d unique tuples across %d files (%d effective, %d crashes)",
len(counter),
len(files),
effective,
len(crashes),
)
all_unique = counter.most_common()
logger.info("Processing candidates and writing output")
already_have = set()
count = 0
def save_file(idx):
input_path = files[idx]
fn = (
base64.b16encode(hash_list[idx]).decode("utf8").lower()
if not args.no_dedup
else os.path.basename(input_path)
)
if args.as_queue:
if args.no_dedup:
fn = "id:%06d,orig:%s" % (count, fn)
else:
fn = "id:%06d,hash:%s" % (count, fn)
output_path = os.path.join(args.output, fn)
try:
os.link(input_path, output_path)
except OSError:
shutil.copy(input_path, output_path)
jobs = [[] for i in range(args.workers)]
saved = set()
for t, c in all_unique:
if c != 1:
continue
idx = best_idxes[t]
if idx in saved:
continue
save_file(idx)
saved.add(idx)
count += 1
worker_idx, pos, tuple_count = trace_info[idx]
job = (pos, tuple_count)
jobs[worker_idx].append(job)
trace_packs = []
workers = []
for i in range(args.workers):
pack_name = os.path.join(args.output, ".traces", f"{i}.pack")
trace_f = open(pack_name, "rb")
trace_packs.append(trace_f)
p = CombineTraceWorker(pack_name, jobs[i], result_queue)
p.start()
workers.append(p)
for _ in range(args.workers):
result = result_queue.get()
already_have.update(result)
for t, c in tqdm(list(reversed(all_unique)), ncols=0):
if t in already_have:
continue
idx = best_idxes[t]
save_file(idx)
count += 1
worker_idx, pos, tuple_count = trace_info[idx]
trace_pack = trace_packs[worker_idx]
trace_pack.seek(pos)
result = array.array(tuple_index_type_code)
result.fromfile(trace_pack, tuple_count)
already_have.update(result)
for f in trace_packs:
f.close()
if args.crash_dir:
logger.info("Saving crashes to %s", args.crash_dir)
crash_files = [files[c] for c in crashes]
if args.no_dedup:
# Unless we deduped previously, we have to dedup the crash files
# now.
crash_files, hash_list = dedup(crash_files)
for idx, crash_path in enumerate(crash_files):
fn = base64.b16encode(hash_list[idx]).decode("utf8").lower()
output_path = os.path.join(args.crash_dir, fn)
try:
os.link(crash_path, output_path)
except OSError:
try:
shutil.copy(crash_path, output_path)
except shutil.Error:
# This error happens when src and dest are hardlinks of the
# same file. We have nothing to do in this case, but handle
# it gracefully.
pass
if count == 1:
logger.warning("all test cases had the same traces, check syntax!")
logger.info('narrowed down to %s files, saved in "%s"', count, args.output)
if not os.environ.get("AFL_KEEP_TRACES"):
logger.info("Deleting trace files")
trace_dir = os.path.join(args.output, ".traces")
shutil.rmtree(trace_dir, ignore_errors=True)
if __name__ == "__main__":
main()