19 citations · 24 across the 20 of their papers we have counts for
7 papers · 1 filter
Defending Against Dormant Poisoning Attacks Across Language and Multimodal Agents
Wonjun Lee, Vaidehi Patil, Zaid Khan +4
Recent work shows that attackers can implant dormant malicious behaviors that remain hidden at release but emerge after benign fine-tuning. As foundation models are used as agents,…
"What Happens Locally, Leaks Globally": Detecting Privacy Leakage Risks in MCP Servers
Biwei Yan, Minghui Xu, Yijun Yang +4
The Model Context Protocol (MCP) has rapidly become the de facto standard for connecting large language models (LLMs) to external resources, but it also introduces a class of priva…
Usability as a Weapon: Attacking the Safety of LLM-Based Code Generation via Usability Requirements
Yue Li, Xiao Li, Hao Wu +5
Large Language Models (LLMs) are increasingly used for automated software development, making their ability to preserve secure coding practices critical. In practice, however, many…
AgentDID: Trustless Identity Authentication for AI Agents
Minghui Xu, Xiaoyu Liu, Yihao Guo +3
AI agents are autonomous entities that can be instantiated on demand, migrate across platforms, and interact with other agents or services without continuous human supervision. In…
Give Them an Inch and They Will Take a Mile:Understanding and Measuring Caller Identity Confusion in MCP-Based AI Systems
Yuhang Huang, Boyang Ma, Biwei Yan +5
The Model Context Protocol (MCP) is an open and standardized interface that enables large language models (LLMs) to interact with external tools and services, and is increasingly a…
Don't believe everything you read: Understanding and Measuring MCP Behavior under Misleading Tool Descriptions
Zhihao Li, Boyang Ma, Xuelong Dai +4
The Model Context Protocol (MCP) enables large language models to invoke external tools through natural-language descriptions, forming the foundation of many AI agent applications.…
Low Rank Comes with Low Security: Gradient Assembly Poisoning Attacks against Distributed LoRA-based LLM Systems
Yueyan Dong, Minghui Xu, Qin Hu +5
Low-Rank Adaptation (LoRA) has become a popular solution for fine-tuning large language models (LLMs) in federated settings, dramatically reducing update costs by introducing train…