From Controlled to the Wild: Evaluation of Pentesting Agents for the Real-World
Academic benchmarks for AI pentesting poorly predict real-world effectiveness, suggesting enterprises may misjudge automated attack tool capabilities.
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arXiv:2605.10834v1 Announce Type: cross Abstract: AI pentesting agents are increasingly credible as offensive security systems, but current benchmarks still provide limited guidance on which will perform best in real-world targets. Existing evaluation protocols assess and optimize for predefined goals such as capture-the-flag, remote code execution, exploit reproduction, or trajectory similarity, in simplified or narrow settings. These tools are valuable for measuring bounded capabilities, yet
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