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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.CR2026

VIGIL: Runtime Enforcement of Behavioral Specifications in AI Agent Skills

Ying Li, Yanju Chen, Hongbo Wen +5

Agentic systems increasingly act through third-party skills, allowing model-generated decisions to affect files, communication channels, and cyber-physical devices. These skills of…

cs.CR2026

Safety in Self-Evolving LLM Agent Systems: Threats, Amplification, and Case Studies

Ruixiao Lin, Xinhao Deng, Qingming Li +12

Self-evolving LLM agent systems, which autonomously update their model parameters, memory, tools, and architectures, introduce a qualitatively new threat landscape in which adversa…

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

SkillTrojan: Backdoor Attacks on Skill-Based Agent Systems

Yunhao Feng, Yifan Ding, Yingshui Tan +6

Skill-based agent systems tackle complex tasks by composing reusable skills, improving modularity and scalability while introducing a largely unexamined security attack surface. We…

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…