CyberStrikeAI is an open-source, AI-native platform for cybersecurity operations — penetration testing, CTF challenges and security research — built around autonomous agents. Its philosophy is that intent should become governed execution: you state the objective, agents plan and run the tooling, and every action produces evidence that improves the next operation. The project has earned about 7,900 stars on GitHub and is under active development in 2026.
The platform orchestrates security tools through MCP (Model Context Protocol), letting AI agents chain reconnaissance, scanning, exploitation and reporting steps while a human operator keeps oversight. Rather than a chatbot pasted onto a terminal, CyberStrikeAI is designed as a system of action: operations are executed in a controlled, auditable way, findings are stored as operational memory, and lessons from one engagement feed the planning of the next. It targets the workflow of modern offensive-security teams and CTF players who want agent speed without losing governance — approvals, logs and reproducibility are first-class concepts rather than afterthoughts. The project is written for practitioners: bring your own models and tools, run it in your own environment, and let agents do the repetitive heavy lifting.
CyberStrikeAI is free and open source under the Apache 2.0 license. Your only costs are the models and infrastructure you run it with.
CyberStrikeAI is for penetration testers, red-teamers and CTF competitors who want autonomous agents doing security work under explicit human governance. It should only be used on systems you own or are authorized to test.