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 six previously unknown zero-days - in real-world open-source C and Java projects, and successfully patched 14 of them. The complete CRS is open source at https://github.com/o2lab/afc-crs-all-you-need-is-a-fuzzing-brain. This paper provides a detailed technical description of our CRS, with an emphasis on its LLM-powered components and strategies. Building on AIxCC, we further introduce a public leaderboard for benchmarking state-of-the-art LLMs on vulnerability detection and patching tasks, derived from the AIxCC dataset. The leaderboard is available at https://o2lab.github.io/FuzzingBrain-Leaderboard/.

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References (9)

01SVF: Static Value-Flow Analysissvf-tools
02Patch Generation : Use LLMs to produce a revised version of the function body
03Validation : Ensure compilation, execute POV tests, and run functionality tests
04The AFL++ fuzzing framework | AFLplusplusaflplus
05Honggfuzz
06Bear: Build EARCodeQL
07Diff Creation : Generate a .diff file using Git differential tools
082023. Static Analysis Re-sults Interchange Format (SARIF) Version 2.1.0 Errata 01 . Technical ReportOASIS
092025. AIxCC Final Competition Procedures and Scoring Guideaicyberchallenge.com/final-competition-procedures-and-scoring-guide/

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