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

Cen Zhang, Younggi Park, Fabian Fleischer, Yu-Fu Fu, Jiho Kim +18 more
2/7/2026
cs.CRcs.AI

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Abstract

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. This paper presents the first systematic analysis of AIxCC. Drawing on design documents, source code, execution traces, and discussions with organizers and competing teams, we examine the competition's structure and key design decisions, characterize the architectural approaches of finalist CRSs, and analyze competition results beyond the final scoreboard. Our analysis reveals the factors that truly drove CRS performance, identifies genuine technical advances achieved by teams, and exposes limitations that remain open for future research. We conclude with lessons for organizing future competitions and broader insights toward deploying autonomous CRSs in practice.

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@article{zhang2026sok,
  title  = {SoK: DARPA's AI Cyber Challenge (AIxCC): Competition Design, Architectures, and Lessons Learned},
  author = {Cen Zhang and Younggi Park and Fabian Fleischer and Yu-Fu Fu and Jiho Kim and Dongkwan Kim and Youngjoon Kim and Qingxiao Xu and Andrew Chin and Ze Sheng and Hanqing Zhao and Brian J. Lee and Joshua Wang and Michael Pelican and David J. Musliner and Jeff Huang and Jon Silliman and Mikel Mcdaniel and Jefferson Casavant and Isaac Goldthwaite and Nicholas Vidovich and Matthew Lehman and Taesoo Kim},
  year   = {2026},
  eprint = {2602.07666},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2602.07666v2}
}

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