BruteForceAI - AI Security Tool

Overview

BruteForceAI is an open-source, LLM-powered penetration-testing utility that automates login attacks and performs form analysis to help security practitioners evaluate authentication hardening. According to the GitHub repository, the project describes itself as an automation tool that leverages large language models to generate and adapt brute-force payloads and to analyze HTML forms, hidden fields, and token patterns for more effective testing. The repository has attracted attention (1,329 stars and 256 forks), showing community interest in an emerging class of AI-assisted offensive-security tooling. The project is explicitly dual-use: it is intended for authorized penetration testing and security validation, but also carries clear potential for misuse if applied against systems without permission. The repository metadata (license listed as NOASSERTION) and a single listed contributor indicate an early-stage project where users should carefully review code, legal standing, and operational safety before use. According to the GitHub activity, the project had a recent commit as of 2025-11-01, suggesting ongoing maintenance at that time.

GitHub Statistics

• Stars: 1,329
• Forks: 256
• Contributors: 1
• License: NOASSERTION
• Primary Language: Python
• Last Updated: 2025-11-01T02:25:19Z

Repository metrics: 1,329 stars, 256 forks, 1 contributor; license flagged as NOASSERTION. Last recorded commit was 2025-11-01. These indicators show notable community interest but limited maintainer bandwidth, so expect minimal official support and to rely on issue threads or self-directed code review for contributions or troubleshooting.

Installation

Install via pip:

git clone https://github.com/MorDavid/BruteForceAI.git

cd BruteForceAI

pip install -r requirements.txt

Key Features

• LLM-driven payload generation to adapt brute-force attempts based on context
• Automated analysis of HTML login forms, hidden fields, and token patterns
• Orchestrates and automates login attack workflows for penetration testing
• Open-source codebase enabling inspection and extension by security teams
• Explicitly flagged as dual-use—intended for authorized testing only

Community

Active interest (1,329 stars, 256 forks) but a very small maintainer base (1 contributor). Community support and contributions appear limited; users should rely on repository issues and forks for patches and discussion.

Key Information

• Category: Security
• Type: AI Security Tool