ContextualJailbreak: Evolutionary Red-Teaming via Simulated Conversational Priming

ArXi:2605.02647v1 Announce Type: new Large language models (LLMs) remain vulnerable to jailbreak attacks that bypass safety alignment and elicit harmful responses. A growing body of work shows that contextual priming, where earlier turns covertly bias later replies, constitutes a powerful attack surface, with hand-crafted multi-turn scaffolds consistently outperforming single-turn manipulations on capable models.