This paper characterizes three challenges—benchmark vulnerabilities, temporal staleness, and runtime uncertainty—that undermine security evaluations of AI agents and outlines directions for more robust frameworks.
Beyond Rewards in Reinforcement Learning for Cyber Defence
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Measuring Security Without Fooling Ourselves: Why Benchmarking Agents Is Hard
This paper characterizes three challenges—benchmark vulnerabilities, temporal staleness, and runtime uncertainty—that undermine security evaluations of AI agents and outlines directions for more robust frameworks.