NeuroSploit is a Rust-based autonomous penetration-testing framework that coordinates multiple AI models for authorized security assessments. It accepts targets such as URLs, source repositories, applications, hosts, and infrastructure environments. The system performs reconnaissance, selects specialized agents for the discovered attack surface, and runs applicable assessments in parallel. Candidate findings are checked through cross-model validation and supporting tool evidence before being reported. It supports black-box, white-box, gray-box, infrastructure, and AI application security testing modes. NeuroSploit also provides a terminal interface, project memory, configurable model providers, structured reports, and a large library of specialized security agents.
Features
- Multi-model autonomous security assessment
- Black-box, white-box, and gray-box modes
- Host and infrastructure security testing
- Cross-model finding validation
- Mission Control terminal interface
- HTML, PDF, JSON, and Markdown reports