3 papers
cs.CR2026
You Told Me to Do It: Measuring Instructional Text-induced Private Data Leakage in LLM Agents
Ching-Yu Kao, Xinfeng Li, Shenyu Dai +4
High-privilege LLM agents that autonomously process external documentation are increasingly trusted to automate tasks by reading and executing project instructions, yet they are gr…
cs.HC2026
"Are You Sure?": An Empirical Study of Human Perception Vulnerability in LLM-Driven Agentic Systems
Xinfeng Li, Shenyu Dai, Kelong Zheng +4
Large language model (LLM) agents are rapidly becoming trusted copilots in high-stakes domains like software development and healthcare. However, this deepening trust introduces a…
cs.AI2026
AgentAuditor: Human-Level Safety and Security Evaluation for LLM Agents
Hanjun Luo, Shenyu Dai, Chiming Ni +5
Despite the rapid advancement of LLM-based agents, the reliable evaluation of their safety and security remains a significant challenge. Existing rule-based or LLM-based evaluators…