Measuring Security Without Fooling Ourselves: Why Benchmarking Agents Is Hard
The paper discusses the challenges of evaluating AI agents in security-critical roles. It identifies three main issues: benchmark vulnerabilities, temporal staleness, and runtime uncertainty. The authors propose directions for developing more reliable evaluation frameworks.
- ▪The benchmarks used to evaluate AI agents have significant weaknesses.
- ▪Three core challenges undermine security evaluations: benchmark vulnerabilities, temporal staleness, and runtime uncertainty.
- ▪The authors outline practical directions for building more robust evaluation frameworks.
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Computer Science > Cryptography and Security arXiv:2605.22568 (cs) [Submitted on 21 May 2026] Title:Measuring Security Without Fooling Ourselves: Why Benchmarking Agents Is Hard Authors:Sahar Abdelnabi, Chris Hicks, Konrad Rieck, Ahmad-Reza Sadeghi View a PDF of the paper titled Measuring Security Without Fooling Ourselves: Why Benchmarking Agents Is Hard, by Sahar Abdelnabi and 3 other authors View PDF HTML (experimental) Abstract:The benchmarks used to evaluate AI agents in security-critical roles suffer from crucial weaknesses. Building on recent empirical evidence, we characterize three core challenges that undermine security evaluations: benchmark vulnerabilities, temporal staleness, and runtime uncertainty.
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