OTTER: A Red-Teaming System for Toxicity-Evading Jailbreak Prompt Optimization
Production LLMs increasingly rely on toxicity-based moderation filters as a primary defense, assuming that harmful intent correlates with toxic surface wording. We show this assumption is fundamentally brittle: surface toxicity and adversarial intent can be decoupled by replacing as few as five tokens. We present OTTER (Obfuscated Toxicity-Evading Token Evolution for Rewriting), a black-box red-teaming framework requiring only standard API access, directly targeting the practical constraints of industry security audits. Evaluated on 457 AdvBench prompts across four GPT models, OTTER raises average ASR from 7.0% to 84.0%. We further provide the first quantitative analysis of the toxicity--...
| Authors | Jerry Wang, Hsin-Ling Hsu, Yi-Cheng Lai et al. |
|---|---|
| Primary category | cs.CR |
| Published | 19 June 2026 |
| Last updated at source | 19 June 2026 |
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