Geminis 0.1.49

AI-powered Python fuzzer using Gemini and Atheris to automatically generate and execute fuzzing harnesses.

Geminis:

This project creates a LLM-assisted Python fuzzing harness generator designed to leverage large language models like Gemini to automatically build fuzzing harnesses for target Python functions. It uses Google’s Atheris fuzzing engine to dynamically generate and test code, with the aim of uncovering bugs or vulnerabilities in software.

Usage:

geminis
--src-dir /path/to/code
--output-dir /path/to/logs
--prompts-path /path/to/prompts.yaml
--api-key /path/to/api.txt
--prompt prompt-id (base if using given yaml prompts)
--mode functions(classes)
--debug Outputs detailed debug statements
--smell Uses optional radon code smell using the maintainability index

Workflow:

1. Load API key (enviorment variable, file, raw string), verify model.
2. Discover .py files; parse target snippets.
3. (Optional) Filter by maintainability index by radon.
4. Build prompt with Atheris docs + code; send to Gemini.