Restricting the Model, Missing the System: Measurement and Accountability in Offensive AI Governance
We show that the instruments used to measure AI offensive capability fail in two ways: (i) they overstate harm, and (ii) they credit the model with capability that belongs to the surrounding system. We argue that restricting access to a model is therefore necessary but not sufficient and that policy and procurement also need system-level, harm-grounded capability assessment. In June 2026, two frontier models were suspended under US export controls, reportedly prompted by a jailbreak that asked a model to read a codebase and fix its flaws. This finding measured an elicitation \emph{system} of model, prompt, and task. We support our argument with a study of an open-source framework in which...
| Authors | Michael Alexander Riegler, Finn Schwall, Annika Willoch Olstad et al. |
|---|---|
| Primary category | cs.CR |
| Published | 10 May 2026 |
| Last updated at source | 7 October 2026 |
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