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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Record
| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2605.22568 |
| Publication time | Fri, 22 May 2026 19:18:22 +0000 |
| Retrieval time | 2026-05-22T19:32:02.773Z |
| Last seen | 2026-05-22T19:32:02.773Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | RhLKK6mOCmNG |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
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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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv.org.
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