FAR.AI released the ClearHarm jailbreak dataset, focusing on clearly harmful topics such as CBRN

FAR.AI released the jailbreak benchmark ClearHarm, focusing on clearly harmful questions such as CBRN threats. The dataset is now available on HuggingFace, containing 179 prompts in total. The authors argue that existing benchmarks have two types of limitations: many questions are ambiguously harmful and could be answered under frontier model safety policies; others are dual-use questions, where attack methods such as PAP can appear effective simply by rewriting the prompt. ClearHarm includes only single-use queries that can be used solely for attack purposes and should be refused regardless of prompt structure, framing, or context. The dataset was generated by Claude 3.7 Sonnet for candidate categories and examples, with five final categories selected: biological, chemical, nuclear, conventional weapons, and malicious cyber code, with a unified grammatical structure to enable cross-category comparison. The authors state that in internal testing, many jailbreak methods that are effective on existing datasets showed significantly reduced performance in extracting such clearly harmful information, with detailed results to be published in a follow-up paper.