LLM agents exhibit persistent attack-selection biases as fixed traits independent of success rates, with a bias momentum effect that resists steering and yields no performance gain.
Dhir, Sudhit Rao, Kaicheng Yu, Twm Stone, and Daniel Kang
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RealVuln benchmark finds security-specialized scanners outperform general-purpose LLMs and rule-based SAST tools on hand-labeled vulnerable Python code under F3 scoring, with all artifacts released.
A practical evaluation protocol for AI pentesting agents that uses validated vulnerability discovery, LLM semantic matching, and bipartite scoring to assess performance in realistic, complex targets.
xOffense automates penetration testing via a fine-tuned Qwen3-32B LLM in a multi-agent setup with specialized agents for reconnaissance, vulnerability scanning, and exploitation, reporting 79.17% sub-task completion on AutoPenBench and AI-Pentest-Benchmark.
citing papers explorer
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CyBiasBench: Benchmarking Bias in LLM Agents for Cyber-Attack Scenarios
LLM agents exhibit persistent attack-selection biases as fixed traits independent of success rates, with a bias momentum effect that resists steering and yields no performance gain.
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RealVuln: Benchmarking Rule-Based, General-Purpose LLM, and Security-Specialized Scanners on Real-World Code
RealVuln benchmark finds security-specialized scanners outperform general-purpose LLMs and rule-based SAST tools on hand-labeled vulnerable Python code under F3 scoring, with all artifacts released.
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From Controlled to the Wild: Evaluation of Pentesting Agents for the Real-World
A practical evaluation protocol for AI pentesting agents that uses validated vulnerability discovery, LLM semantic matching, and bipartite scoring to assess performance in realistic, complex targets.
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xOffense: An Autonomous Multi-Agent Framework for Penetration Testing with Domain-Adapted Large Language Models
xOffense automates penetration testing via a fine-tuned Qwen3-32B LLM in a multi-agent setup with specialized agents for reconnaissance, vulnerability scanning, and exploitation, reporting 79.17% sub-task completion on AutoPenBench and AI-Pentest-Benchmark.