2 citations · 2 across the 5 of their papers we have counts for
7 papers
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…
Aligning Provenance with Authorization: A Dual-Graph Defense for LLM Agents
Peiran Wang, Ying Li, Yuan Tian
LLM-based agents are increasingly deployed in high-stakes scenarios such as email management, financial transactions, and code execution, where they interact with the external worl…
Reframing LLM Agent Security as an Agent-Human Interaction Problem
Peiran Wang, Ying Li, Yuan Tian
We argue that LLM agent security is fundamentally an agent-human interaction (AHI) problem, not a purely algorithmic one. To substantiate this position, we conduct a systematic ana…
Securing LLM Agents Need Intent-to-Execution Integrity
Wenjie Qu, Ming Xu, Peiran Wang +3
This position paper argues that securing LLM agents requires first defining an end-to-end correctness property that specifies when an agent's execution faithfully reflects the user…
Options, Not Clicks: Lattice Refinement for Consent-Driven MCP Authorization
Ying Li, Yanju Chen, Peiran Wang +4
As Model Context Protocol adoption grows, securing tool invocations via meaningful user consent has become a critical challenge, as existing methods, broad always allow toggles or…
From Docs to Descriptions: Smell-Aware Evaluation of MCP Server Descriptions
Peiran Wang, Ying Li, Yuqiang Sun +3
The Model Context Protocol (MCP) has rapidly become a de facto standard for connecting LLM-based agents with external tools via reusable MCP servers. In practice, however, server s…