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Creating fuzz driver for Python libraries using LibFuzzer. This skill is useful when agent needs to work with creating fuzz drivers / fuzz targets for Python project and libraries.
Fuzz testing for Python projects are Atheris. Atheris is a coverage-guided Python fuzzing engine. It supports fuzzing of Python code, but also native extensions written for CPython. Atheris is based off of libFuzzer. When fuzzing native code, Atheris can be used in combination with Address Sanitizer or Undefined Behavior Sanitizer to catch extra bugs.
You can install prebuilt versions of Atheris with pip:
pip3 install atheris
These wheels come with a built-in libFuzzer, which is fine for fuzzing Python code. If you plan to fuzz native extensions, you may need to build from source to ensure the libFuzzer version in Atheris matches your Clang version.
#!/usr/bin/python3
import atheris
with atheris.instrument_imports():
import some_library
import sys
def TestOneInput(data):
some_library.parse(data)
atheris.Setup(sys.argv, TestOneInput)
atheris.Fuzz()
When fuzzing Python, Atheris will report a failure if the Python code under test throws an uncaught exception.
npx skills add benchflow-ai/skillsbench --skill fuzzing-pythonHow clear and easy to understand the SKILL.md instructions are, rated from 1 to 5.
Mostly clear, but there are still a few confusing or poorly structured parts.
How directly an agent can act on the SKILL.md instructions, rated from 1 to 5.
Partially actionable with several concrete steps, but still missing important details.