Atheris is a coverage-guided fuzzer for Python that helps developers find bugs and security vulnerabilities by automatically generating complex inputs.

Can this skill test C-extensions in Python?

Yes, Atheris is specifically designed to find bugs in both pure Python code and native extensions written in C or C++.

How does the Atheris skill improve Claude's behavior?

This skill provides Claude with domain-specific knowledge and best practices for implementing and configuring fuzz tests using the Atheris framework.

Is this skill suitable for general unit testing?

While related, Atheris focuses on fuzzing—a form of automated testing that searches for edge cases and crashes rather than just verifying expected outcomes.

Who developed the Atheris skill?

This skill was developed by the security experts at Trail of Bits as part of their security testing handbook skills collection.

Atheris Python Fuzzing

Name: Atheris Python Fuzzing
Author: plurigrid

byplurigrid

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Security & Testing

Discovers vulnerabilities and edge-case bugs in Python code using Atheris coverage-guided fuzzing.

About

The Atheris skill empowers Claude to perform security-focused testing by integrating the Atheris fuzzing engine into the development workflow. Created by security experts at Trail of Bits, this skill provides specialized patterns and guidance for writing effective fuzz tests, identifying memory corruption issues, and detecting logic vulnerabilities in Python applications. It is particularly valuable for developers looking to harden their codebases against unexpected inputs and ensure high-level security standards through automated input generation.

Key Features

Integration with security auditing and variant analysis
Detection of security vulnerabilities and crash-inducing bugs
Automated input generation for edge-case discovery
Coverage-guided fuzzing for Python applications
2 GitHub stars
Support for testing native Python C/C++ extensions

Use Cases

Stress testing data parsing libraries for unexpected crashes
Finding memory safety issues in Python C-extensions
Hardening Python APIs against malicious or malformed input

About

Key Features

Integration with security auditing and variant analysis
Detection of security vulnerabilities and crash-inducing bugs
Automated input generation for edge-case discovery
Coverage-guided fuzzing for Python applications
2 GitHub stars
Support for testing native Python C/C++ extensions

Use Cases

Stress testing data parsing libraries for unexpected crashes
Finding memory safety issues in Python C-extensions
Hardening Python APIs against malicious or malformed input