While Deep Neural Networks (DNNs) have achieved remarkable progress in cutting-edge domains, their inherent brittleness has become a growing concern. To ensure the reliability and safety of DNN-enabled software, DNN testing has emerged as an indispensable practice. Within this context, test input prioritization is esse...
Hao-Ran Li, Shi-Hai Wang, Bin Liu et al.· 0 citations
Autonomous AI agents tackling Long Horizon Tasks depend on marketplace skills that are certified one at a time: a scanner returns a safety verdict for each skill and declares the ecosystem safe if every package passes. We show that this assumption fails under skill composition. A skill may pass the per-skill scanner in...
Ming-Xiao Liu, Zhoumian Jiang, Jia-Nan Ma et al.· 0 citations
Self-evolving skill (SES) systems distill agent trajectories into persistent skills, allowing untrusted experience to become trusted instruction. We introduce PoisonedEvolution, a trajectory-poisoning attack on this promotion process. Our skill-visible black-box attacker can inspect a target skill and contribute bounde...
Jia-Luo Chen, Lingqi Jiang, Xin-Hao Deng et al.· 0 citations
SKILLTRACE is presented, a multi-trace provenance auditing framework for LLM-agent skill reuse that represents the Operational Trace as a Skill Operational Graph (SOG) that captures activation, procedure, and resource-flow structure.
Jia-Luo Chen, Minghe Wang, Lingqi Jiang et al.· 0 citations
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