Interactive Backdoor Attacks in LLM-Based Proactive Dialogue Systems

LLM-based proactive dialogue systems provide goal-directed support through sustained interaction. Fine-tuning these models on externally supplied dialogue data introduces backdoor risks. An interactive backdoor attack framework uses training-data poisoning to steer post-trigger, multi-turn interactions toward an attacker-specified objective.