ATLANTIS: AI-driven Threat Localization, Analysis, and Triage Intelligence System
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Abstract (arXiv)
We present ATLANTIS, the cyber reasoning system developed by Team Atlanta that won 1st place in the Final Competition of DARPA's AI Cyber Challenge (AIxCC) at DEF CON 33 (August 2025). AIxCC (2023-2025) challenged teams to build autonomous cyber reasoning systems capable of discovering and patching vulnerabilities at the speed and scale of modern software. ATLANTIS integrates large language models (LLMs) with program analysis -- combining symbolic execution, directed fuzzing, and static analysis -- to address limitations in automated vulnerability discovery and program repair. Developed by researchers at Georgia Institute of Technology, Samsung Research, KAIST, and POSTECH, the system addresses core challenges: scaling across diverse codebases from C to Java, achieving high precision while maintaining broad coverage, and producing semantically correct patches that preserve intended behavior. We detail the design philosophy, architectural decisions, and implementation strategies behind ATLANTIS, share lessons learned from pushing the boundaries of automated security when program analysis meets modern AI, and release artifacts to support reproducibility and future research.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Sep 2025.
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Citing papers per year: 2025: 1; 2026: 8.
9 papers.
- 2026SoK: DARPA's AI Cyber Challenge (AIxCC): Competition Design, Architectures, and Lessons Learnedcited by 9
- 2026Patch-to-PoC: A Systematic Study of Agentic LLM Systems for Linux Kernel N-Day Reproductioncited by 7
- 2025PBFuzz: Agentic Directed Fuzzing for PoV Generationcited by 4
- 2026OpenSage: Self-programming Agent Generation Enginecited by 4
- 2026Execution-State-Aware LLM Reasoning for Automated Proof-of-Vulnerability Generationcited by 3
- 2026Revelio: Cost-Efficient Agentic Memory Safety Vulnerability Detection For Repository-Scale Codebasescited by 1
- 2026Agentic Vulnerability Reasoning on COTS Binariescited by 0
- 2026Code-Augur: Agentic Vulnerability Detection via Specification Inferencecited by 0
- 2026BlueSTAR: Tiered Agentic Architecture for Autonomous Cyber Defensecited by 0
- 2026BlueSTAR: Tiered Agentic Architecture for Autonomous Cyber Defense10 Sep 2026
- 2026Revelio: Cost-Efficient Agentic Memory Safety Vulnerability Detection For Repository-Scale Codebases20 Jun 2026
- 2026Code-Augur: Agentic Vulnerability Detection via Specification Inference17 Jun 2026
- 2026Agentic Vulnerability Reasoning on COTS Binaries6 May 2026
- 2026OpenSage: Self-programming Agent Generation Engine18 Feb 2026
- 2026Execution-State-Aware LLM Reasoning for Automated Proof-of-Vulnerability Generation14 Feb 2026
- 2026SoK: DARPA's AI Cyber Challenge (AIxCC): Competition Design, Architectures, and Lessons Learned7 Feb 2026
- 2026Patch-to-PoC: A Systematic Study of Agentic LLM Systems for Linux Kernel N-Day Reproduction7 Feb 2026
- 2025PBFuzz: Agentic Directed Fuzzing for PoV Generation4 Dec 2025