BruteForceAI is an open-source security testing tool that applies large language models to the analysis of login forms and authentication flows in web applications. At a high level, the project uses AI to inspect HTML content, identify the relevant form elements, and automate selector discovery so that a tester does not need to hand-map every field before evaluation. It combines that analysis layer with automated credential testing workflows, framing itself as a more adaptive alternative to older brute-force tooling that depends heavily on manual configuration. The repository emphasizes features such as threaded execution, logging, and notification integrations, which position it as an automation-oriented project for controlled security assessment environments. From a software design perspective, its distinguishing idea is the use of language models as a front-end analysis layer that interprets a target page before the rest of the workflow proceeds.
Features
- LLM-based analysis of HTML to identify login form selectors
- Automated selector discovery to reduce manual configuration
- Support for multi-threaded execution workflows
- Human-like timing controls with jitter and randomized behavior
- Webhook integrations for external notifications and reporting
- SQLite-based logging for tracking assessment activity