A systematization of knowledge paper that taxonomizes honeypot detection vectors, synthesizes LLM-honeypot literature into canonical architecture and evaluation methods, and proposes a roadmap for autonomous deception systems.
Frontier ai’s impact on the cybersecurity landscape
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CyberGym-E2E is a new end-to-end benchmark that evaluates AI agents on vulnerability discovery, PoC generation, and patch generation using 920 real-world cases from open-source projects.
LLM-assisted mutation testing reproduced 10 of 13 known PKCS#1 v1.5 violation categories and one new discrepancy but was limited by 82.5% hallucination rate in generated scripts.
Cybersecurity's scale, adversaries, labeling issues, and operational demands make it the superior test-case for general AI progress over NLP or computer vision.
citing papers explorer
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SoK: Honeypots & LLMs, More Than the Sum of Their Parts?
A systematization of knowledge paper that taxonomizes honeypot detection vectors, synthesizes LLM-honeypot literature into canonical architecture and evaluation methods, and proposes a roadmap for autonomous deception systems.
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CyberGym-E2E: Scalable Real-World Benchmark for AI Agents' End-to-End Cybersecurity Capabilities
CyberGym-E2E is a new end-to-end benchmark that evaluates AI agents on vulnerability discovery, PoC generation, and patch generation using 920 real-world cases from open-source projects.
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Evaluating the Effectiveness of LLMs in Aiding Compliance Testing of PKCS#1-v1.5
LLM-assisted mutation testing reproduced 10 of 13 known PKCS#1 v1.5 violation categories and one new discrepancy but was limited by 82.5% hallucination rate in generated scripts.
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Cybersecurity is the True Frontier for Generative AI Success or Failure
Cybersecurity's scale, adversaries, labeling issues, and operational demands make it the superior test-case for general AI progress over NLP or computer vision.