A Red-Team Study of Anthropic Fable 5 & Opus 4.8 Models
We evaluate the adversarial robustness of three frontier large language models (LLMs) developed by Anthropic, Opus 4.8, Fable 5 and its successor Fable 5.1, against four families of automated jailbreak attack across 7,826 harmful intents spanning a ten-category harm taxonomy. Using the HackAgent red-teaming framework, hundreds of thousands of adversarial attempts were generated and every apparent success was independently re-adjudicated by the same panel of five frontier judge models ($\geq 4/5$ agreement) for all three targets. All models resist the majority of attacks, but the residual surface is larger than aggregate framing suggests: it is dominated by adaptive iterative attacks, whil...
| Authors | Nicola Franco |
|---|---|
| Primary category | cs.CR |
| Published | 16 June 2026 |
| Last updated at source | 20 September 2026 |
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