collaborators
Showing cs.CRShow all

6 papers · 1 filter

cs.CR2026

FlowGuard: From Signals to Evidence for MCP Security Detection

Baichao An, Pei Chen, Geng Hong +2

The Model Context Protocol (MCP) enables LLM agents to interact with external tools through metadata exchange, tool invocation, and response consumption. Existing MCP security scan…

cs.CR2026

Rethinking MCP Security: A Large-Scale Study of Runtime MCP Servers and Security Scanner Reliability

Pei Chen, Baichao An, Mengying Wu +6

The Model Context Protocol (MCP) has rapidly established itself as a standard interface for enabling LLM-based agents to interact with external tools and services. As MCP servers a…

cs.CR2026

Unveiling the Resilience of LLM-Enhanced Search Engines against Black-Hat SEO Manipulation

Pei Chen, Geng Hong, Xinyi Wu +6

The emergence of Large Language Model-enhanced Search Engines (LLMSEs) has revolutionized information retrieval by integrating web-scale search capabilities with AI-powered summari…

cs.CR2025

MCPZoo: A Large-Scale Dataset of Runnable Model Context Protocol Servers for AI Agent

Mengying Wu, Pei Chen, Geng Hong +6

Model Context Protocol (MCP) enables agents to interact with external tools, yet empirical research on MCP is hindered by the lack of large-scale, accessible datasets. We present M…

cs.CR2025

PRISON: Unmasking the Criminal Potential of Large Language Models

Xinyi Wu, Geng Hong, Pei Chen +3

As large language models (LLMs) advance, concerns about their misconduct in complex social contexts intensify. Existing research overlooked the systematic understanding and assessm…

cs.CR2025

You Can't Eat Your Cake and Have It Too: The Performance Degradation of LLMs with Jailbreak Defense

Wuyuao Mai, Geng Hong, Pei Chen +5

With the rise of generative large language models (LLMs) like LLaMA and ChatGPT, these models have significantly transformed daily life and work by providing advanced insights. How…