collaborators

6 papers

cs.CR2026

When Experience Becomes Instruction: Trajectory Poisoning in Self-Evolving Agent Skill Systems

Jialuo Chen, Lingqi Jiang, Xinhao Deng +7

Self-evolving skill (SES) systems distill agent trajectories into persistent skills, allowing untrusted experience to become trusted instruction. We introduce PoisonedEvolution, a…

cs.AI2026

SkillTrace: Multi-Trace Provenance Auditing for LLM-Agent Skill Reuse

Jialuo Chen, Minghe Wang, Lingqi Jiang +7

LLM-agent ecosystems are rapidly growing around reusable skills: mixed-modality packages of metadata, natural-language instructions, code, tools, references, and operational workfl…

cs.AI2026

Safety Testing LLM Agents at Scale: From Risk Discovery to Evidence-Grounded Verification

Yunhao Feng, Ruixiao Lin, Ming Wen +12

LLM agents increasingly perform autonomous actions through external tools, leading to complex and evolving safety risks. However, existing safety testing targets expert-designed sa…

cs.CR2026

BraveGuard: From Open-World Threats to Safer Computer-Use Agents

Yunhao Feng, Xiaohu Du, Xinhao Deng +13

Computer-use agents extend language models from text generation to sustained interaction with files, terminals, browsers, and external tools. This shift creates safety risks that a…

cs.CR2026

ASEval: Automated Trajectory-Level Security Testing for Autonomous Agents

Jianan Ma, Xiaohu Du, Ruixiao Lin +9

As autonomous agents (e.g., OpenClaw) increasingly operate with deep system-level privileges to execute complex tasks, they introduce severe, unmitigated security risks. Existing L…

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…