EvoJail: Evolutionary Diverse Jailbreak Prompt Generation for Large Language Models
As LLMs continue to shape real-world applications, automated jailbreak generation becomes essential to reveal safety weaknesses and guide model improvement. Existing automatic jailbreak generation methods have not yet fully considered two important aspects: adaptability to evolving safety-finetuned models, which affects their effectiveness on newer model versions, and diversity in generated prompts, which can cause narrow or repetitive attack patterns. To address these issues, we propose EvoJail, an instruction-fusion-driven evolutionary jailbreak generation framework that formalizes jailbreak prompt generation as a multi-objective black-box optimization problem and leverages the principl...
| Authors | Rui Tang, Kaiyu Xu, Pengsen Cheng et al. |
|---|---|
| Primary category | cs.NE |
| Published | 22 April 2026 |
| Last updated at source | 22 April 2026 |
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