SOURCE-LINKED INTELLIGENCE
The Safeguard Worked. Is the LLM System Safer?
Safeguards in deployed LLM services are evaluated by refusal, attack success, and policy violation rates. Those rates characterize how a control performed on the requests it was tested on. A deployment has to answer a different question: how much help with harmful tasks the service still gives an attacker who keeps adapting or finds another way in. We determine what each reported result implies for that question, allowing results from different safeguard families to be compared under one deployment criterion. The evidence requirements are strongly asymmetric. One attack that obtains harmful he
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-01T00:38:35.000Z
First collected: 2026-09-21T06:21:59.299Z. This is not the publication date.