3 papers
cs.CR2026
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…
cs.AI2026
Beyond Single-Use Tokens: Durable Authorization State for Replay-Resistant LLM Agent Actions
Jinghan Xu, Longze Fan, Zeyuan Wang +2
Tool-using large language model agents frequently replan, retry failed operations, delegate tasks, and resume after crashes. These behaviors can cause one user authorization to be…
cs.CR2026
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…