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fuzzing-python

Automate fuzz testing of Python code with Atheris instrumentation.

Updated Jan 15, 2026
Search Tags:#testing#python#fuzzing#native-extensions#atheris#crashes#libfuzzer
One-click install
npx skills add https://github.com/KaiserWhoLearns/skillsbench --skill fuzzing-python
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fuzzing-python
Source: https://github.com/KaiserWhoLearns/skillsbench/tree/main/tasks/setup-fuzzing-py/environment/skills/fuzzing-python
Command: npx skills add https://github.com/KaiserWhoLearns/skillsbench --skill fuzzing-python

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Fuzzing Python code helps uncover crashes and security issues by automatically generating inputs and exploring edge cases that are difficult to reach with traditional tests.

Core Features & Use Cases

  • Coverage-guided fuzzing for Python code using Atheris, including native extensions.
  • Instrumentation and quick-start workflow: write a fuzz target that consumes bytes and run Setup() + Fuzz() for continuous testing.
  • Use Case: Detect crashes in Python libraries, parsing, and CPython extensions before deployment.

Quick Start

Write a small fuzzer entry point, instrument imports as needed with Atheris, call atheris.Setup() with your program arguments, and then invoke atheris.Fuzz() to begin fuzzing.

Frequently Asked Questions about fuzzing-python

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I fuzz Python code to find crashes and security issues?▼

Fuzzing Python code automatically generates inputs to explore edge cases and uncover crashes. This Skill automates coverage-guided fuzzing using Atheris to instrument imports and run fuzzers against Python targets.

How do I start fuzzing a Python library with Atheris?▼

To start fuzzing with Atheris, write a fuzz target that consumes bytes, instrument imports as needed, call atheris.Setup() with your program arguments, and then invoke atheris.Fuzz() to begin continuous testing.

Can I use Atheris fuzzing for Python projects with native extensions?▼

Atheris fuzzing supports Python libraries and applications including those with native CPython extensions. It instruments native code to provide coverage-guided fuzzing across unit tests, CI pipelines, and OSS fuzz projects.

What are the requirements to run fuzz tests on my Python project?▼

Running fuzz tests requires the atheris package, a valid fuzz target function signature that consumes bytes, and a Setup and Fuzz workflow configured to run repeatedly in your testing environment.

How does coverage-guided fuzzing improve Python testing?▼

Coverage-guided fuzzing improves Python testing by automatically generating inputs and exploring edge cases that are difficult to reach with traditional tests, effectively detecting crashes in parsing and library code before deployment.

Why should I integrate fuzzing into my Python CI pipeline?▼

Integrating fuzzing into your Python CI pipeline automates the detection of crashes and security issues by continuously running fuzzers against your targets, uncovering edge cases before deployment.

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