4 papers · 1 filter
Convergent Detour Hijacking: Task-Preserving Resource Amplification in Skill-Based LLM Agents
Junliang Liu, Ruoyu Li, Wenxin Tang +4
LLM agents increasingly rely on third-party skills, using natural-language descriptions for selection and instruction bodies for planning. This progressive-disclosure design expose…
MNC: Scope-Bound Semantic Declassification for Private LLM-Agent Communication
Jinghan Xu, Longze Fan, Zeyuan Wang +2
Multi-agent large language model (LLM) systems can expose protected state through internal messages, tool arguments, logs, and persistent memory even when their public outputs appe…
Policy-Backed Selective Regeneration under Tainted Inter-Agent Communication
Jinghan Xu, Longze Fan, Zeyuan Wang +2
Inter-agent communication is essential to multi-agent language-model systems, yet a single message may combine task-critical information with instructions not authorized by the ori…
Memory Provenance Laundering in LLM Agents: A Non-Amplification Firewall for Persistent Memory
Jinghan Xu, Yiyong Xiao, Wanru Shao +2
Long-term memory lets large language model(LLM) agents reuse prior preferences and work flows, but it also turns untrusted observations into persistent action context. We identify…