STRIATUM-CTF: A Protocol-Driven Agentic Framework for General-Purpose CTF Solving

Large Language Models LLMs have demonstrated potential in code generation, yet they struggle with the multi-step, stateful reasoning required for offensive cybersecurity operations. Existing research often relies on static benchmarks that fail to capture the dynamic nature of real-world...

OSS-CRS: Liberating AIxCC Cyber Reasoning Systems for Real-World Open-Source Security

DARPA's AI Cyber Challenge AIxCC showed that cyber reasoning systems CRSs can go beyond vulnerability discovery to autonomously confirm and patch bugs: seven teams built such systems and open-sourced them after the competition. Yet all seven open-sourced CRSs remain largely unusable outside their...

SoK: DARPA'S AI Cyber Challenge (AIxCC): Competition Design, Architectures, and Lessons Learned

DARPA's AI Cyber Challenge AIxCC, 2023--2025 is the largest competition to date for building fully autonomous cyber reasoning systems CRSs that leverage recent advances in AI -- particularly large language models LLMs -- to discover and remediate vulnerabilities in real-world open-source software...

All You Need Is a Fuzzing Brain: an LLM-Powered System for Automated Vulnerability Detection and Patching

Our team, All You Need Is A Fuzzing Brain, was one of seven finalists in DARPA's Artificial Intelligence Cyber Challenge AIxCC, placing fourth in the final round. During the competition, we developed a Cyber Reasoning System CRS that autonomously discovered 28 security vulnerabilities - including...