This repository provides a specialized wordlist, bbFuzzing.txt, designed for web application security testing, particularly for discovering hidden files, directories, and misconfigurations. It is primarily targeted at security researchers and penetration testers looking to enhance their fuzzing efforts with AI-generated payloads.

How It Works

The core of this project is the bbFuzzing.txt wordlist, which is claimed to be 90% generated using OpenAI's ChatGPT. This AI-driven approach aims to produce a more diverse and potentially effective set of fuzzing strings compared to traditional, manually curated lists. The README also includes numerous examples of how to integrate this wordlist with tools like ffuf and nuclei to perform targeted scans, filter false positives, and identify specific vulnerabilities like configuration exposures.

Quick Start & Requirements

• Install/Run: Download the bbFuzzing.txt file. Usage involves integrating it with fuzzing tools.
• Prerequisites: Requires a fuzzing tool like ffuf (Fast User Enumeration Fuzzer) and potentially nuclei for vulnerability scanning. Python 3 is recommended for associated scripts.
• Links:
  • ffuf: https://github.com/ffuf/ffuf
  • nuclei: https://github.com/projectdiscovery/nuclei

Highlighted Details

• Wordlist 90% generated by OpenAI ChatGPT for enhanced fuzzing diversity.
• Extensive examples for ffuf demonstrating various fuzzing techniques (path traversal, encoding, host header manipulation).
• Includes methods for filtering false positives using ffuf and httpx.
• Mentions tools and techniques for bypassing 401/403 status codes.

Maintenance & Community

The repository is maintained by rewwardius. There are no explicit links to community channels or a roadmap provided in the README.

Licensing & Compatibility

The repository does not specify a license. The included tools (ffuf, nuclei, etc.) have their own licenses, which should be reviewed for compatibility.

Limitations & Caveats

The effectiveness of an AI-generated wordlist can vary, and it may require significant tuning and filtering to reduce false positives. The README does not provide benchmarks or comparative analysis against other wordlists. The project is presented as a resource rather than a standalone tool, requiring integration with other security testing utilities.