AI Security Leaderboard: Methodology, Results and Minimal Standard
We introduce the this http URL Minimal Standard for Safeguards, Version 1.0: a taxonomy of 67 readily accessible static jailbreak techniques, a method for composing them into a very large attack space, and a benchmark of flagship models against a sample of it. We also introduce a cost-to-jailbreak metric that models attacker spend directly, with right-censored lower bounds where no universal jailbreak was found. Robustness is highly uneven: the cost to break these models varies over a hundredfold.
- ▪We introduce the this http URL Minimal Standard for Safeguards, Version 1.0: a taxonomy of 67 readily accessible static jailbreak techniques, a method for composing them into a very large attack space, and a benchmark of flagship models aga
- ▪We also introduce a cost-to-jailbreak metric that models attacker spend directly, with right-censored lower bounds where no universal jailbreak was found.
- ▪Robustness is highly uneven: the cost to break these models varies over a hundredfold.
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Story provenance
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Record
| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2608.03070 |
| Publication time | Wed, 05 Aug 2026 17:07:10 +0000 |
| Retrieval time | 2026-08-05T17:15:47.417Z |
| Last seen | 2026-08-05T17:15:47.417Z |
| 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 | vlFE-5K_0tA8 · 1 stories |
| 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 |
Rights status (four layers)
WeSearch handling by dimension
| 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:2608.03070 (cs) [Submitted on 4 Aug 2026] Title:AI Security Leaderboard: Methodology, Results and Minimal Standard Authors:Jasper Timm, Lukas Struppek, Ziwei Xu, Grace Cheong, Oscar Mata, Dan Zhao, Mick Yang, Isadora De Andrade, Xiaojun Jia, Yiming Li, Samuel Bauer, Heather McIntyre, Adam Gleave, Edward Yee, Kellin Pelrine View a PDF of the paper titled AI Security Leaderboard: Methodology, Results and Minimal Standard, by Jasper Timm and 14 other authors View PDF Abstract:Frontier AI model developers increasingly rely on layered safeguards to prevent catastrophic misuse, but little public evidence exists on how much protection these safeguards provide, or how consistently across developers.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv.org.
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