Skip to main content

Coverage-guided fuzz testing for Python

Project description

CobraFuzz: Parallel coverage-guided fuzz testing for Python

Makefile CI CodeQL

CobraFuzz is a parallel coverage-guided fuzzer for testing Python programs. It is a fork of pythonfuzz.

Fuzzing for safe languages like Python is a powerful strategy for finding bugs like unhandled exceptions, logic bugs and security bugs. It makes a good addition to classic unit-testing.

Usage

Fuzz Target

The first step is to implement a function to be fuzz-tested, also called a fuzz target. Here is an example of a simple fuzz target for the built-in html module

from cobrafuzz.main import CobraFuzz


@CobraFuzz
def fuzz(buf: bytes) -> None:
    from html.parser import HTMLParser

    try:
        parser = HTMLParser()
        parser.feed(buf.decode("ascii"))
    except UnicodeDecodeError:
        pass


if __name__ == "__main__":
    fuzz()

Features of a fuzz target:

  • fuzz() will call the fuzz target in an infinite loop with random data generated by the coverage-guided algorithm. The data is passed to the target in a separate process through the buf parameter.
  • The function must catch and ignore any expected exceptions that arise when passing invalid input to the tested program.
  • The fuzz target must call the test function / library with the passed buffer or a transformation on the test buffer if the structure is different or of different type.
  • Fuzz functions can also implement application level checks to catch application or logical bugs. For example: decode the buffer with the library under test, encode it again, and check that both results are equal. To communicate the result, the fuzz target should throw an exception.
  • CobraFuzz will report any unhandled exceptions as crashes.

Running

The next step is to download CobraFuzz and then run the fuzzer:

$ pip install cobrafuzz
[...]

$ python examples/fuzz_htmlparser/fuzz.py --crash-dir results fuzz --max-crashes 1
#0 READ units: 1 workers: 7 seeds: 1
#1 NEW     cov: 279 corp: 1 exec/s: 89 crashes: 0
#5 NEW     cov: 366 corp: 2 exec/s: 299 crashes: 0
#7 NEW     cov: 401 corp: 3 exec/s: 3124 crashes: 0
[...]
#154382 NEW     cov: 1086 corp: 50 exec/s: 22835 crashes: 0
#156521 NEW     cov: 1092 corp: 51 exec/s: 2797 crashes: 0
Crash dir created (results)
sample was written to results/crash-c76ab601df7d8513560ad3c1a38f43c715122b342637a4517a32d13dea03d3ce
sample = 3c215b2119
Found 1 crashes, stopping.

By default, CobraFuzz will use all CPUs available in the system (8 in this example: 1 coordination process and 7 independent workers). Use the -j / --num-workers command line parameter to override the default. In this example an unhandled exception is found in a few seconds.

Corpus

CobraFuzz will generate and test various inputs in an infinite loop.

Seeds can be provided as a mix of files and directories by the seeds parameter. If one of those seeds parameters is a directory, all regular files therein are used as seeds. CobraFuzz can also start with an empty seed corpus, though some valid test-cases in the seed corpus may speed up the fuzzing substantially.

More fuzz target examples (for real and popular libraries) can be found in the examples directory.

Credits & Acknowledgments

CobraFuzz is a fork of pythonfuzz. pythonfuzz is a port of fuzzitdev/jsfuzz. jsfuzz is in turn heavily based on go-fuzz originally developed by Dmitry Vyukov. go-fuzz is in turn heavily based on Michal Zalewski's AFL.

Contributions

Contributions are welcome, feel free to open issues and pull requests on GitHub.

Trophies

Feel free to add bugs that you found with CobraFuzz to this list via pull requests.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cobrafuzz-2.3.0.tar.gz (26.2 kB view details)

Uploaded Source

Built Distribution

cobrafuzz-2.3.0-py3-none-any.whl (26.0 kB view details)

Uploaded Python 3

File details

Details for the file cobrafuzz-2.3.0.tar.gz.

File metadata

  • Download URL: cobrafuzz-2.3.0.tar.gz
  • Upload date:
  • Size: 26.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.9.19

File hashes

Hashes for cobrafuzz-2.3.0.tar.gz
Algorithm Hash digest
SHA256 5cc5201d0be38dfc5baec5c004a5b8d40b3fa25710422c171c5d7d2b770aabb8
MD5 fb77f43dee476b81c067dca180d5f385
BLAKE2b-256 ec76f66a6699bb0733a3cd60b862305a7ca54eae1878305c5a70066136a9ef87

See more details on using hashes here.

File details

Details for the file cobrafuzz-2.3.0-py3-none-any.whl.

File metadata

  • Download URL: cobrafuzz-2.3.0-py3-none-any.whl
  • Upload date:
  • Size: 26.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.9.19

File hashes

Hashes for cobrafuzz-2.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 2ff292c50c3e1cee3ca6acc6dfacad99474ae3757a52bde22e67b5d856b86ece
MD5 18893d10d3ba8e0b33ee6c4aaf38d6db
BLAKE2b-256 4b98a391c22487a4fd9a9ce95d8639d0d01266905baa3972985b0ababa835c69

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page