Xiaofang Yang

LLM-powered autonomous agents are alarmingly susceptible to multi-turn, context-aware attacks that bypass standard security measures, nearly doubling the risk trigger rate.

Autonomous LLM agents are riddled with vulnerabilities, as point defenses fail to address cross-temporal and multi-stage systemic risks like memory poisoning and intent drift.