Multi-Turn Jailbreak Attacks

Multi-turn jailbreak research studies how attackers use conversation history to make harmful requests seem benign, build persuasive context, or divide a task into seemingly safe steps. Common approaches include simulated dialogue, psychological persuasion, evolutionary search, and reinforcement learning, evaluated on harmful-behavior benchmarks and in medical, multimodal, and tool-using settings. Defenses range from turn-level monitors and cumulative-risk scoring to classifiers, provenance tracking, and response rewriting. A central tension is that single-turn checks miss risks that emerge over time, while earlier intervention can increase false alarms or constrain useful responses; evaluation also depends on reliable judges and comparable attack budgets.