collaborators

8 papers

cs.CR2026

Measuring the Security of Mobile LLM Agents under Adversarial Prompts from Untrusted Third-Party Channels

Chenghao Du, Quanfeng Huang, Tingxuan Tang +3

Large Language Models (LLMs) have transformed software development, enabling AI-powered applications known as LLM-based agents that promise to automate tasks across diverse apps an…

cs.CR2026

AgentWard: A Lifecycle Security Architecture for Autonomous AI Agents

Yixiang Zhang, Xinhao Deng, Jiaqing Wu +3

Autonomous AI agents extend large language models into full runtime systems that load skills, ingest external content, maintain memory, plan multi-step actions, and invoke privileg…

cs.CR2026

How Far Should We Need to Go : Evaluate Provenance-based Intrusion Detection Systems in Industrial Scenarios

Yue Xiao, Ling Jiang, Sen Nie +4

Provenance-based Intrusion Detection Systems (PIDSes) have been widely used to detect Advanced Persistent Threats (APTs). Although many studies achieve high performance in the eval…

cs.CR2026

Taming OpenClaw: Security Analysis and Mitigation of Autonomous LLM Agent Threats

Xinhao Deng, Yixiang Zhang, Jiaqing Wu +15

Autonomous Large Language Model (LLM) agents, exemplified by OpenClaw, demonstrate remarkable capabilities in executing complex, long-horizon tasks. However, their tightly coupled…

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.CR2026

Understanding Human-AI Collaboration in Cybersecurity Competitions

Tingxuan Tang, Nicolas Janis, Kalyn Asher Montague +6

Capture-the-Flag (CTF) competitions are increasingly becoming a testbed for evaluating AI capabilities at solving security tasks, due to the controlled environments and objective s…