10 papers
Bad company corrupts good morals: Understanding and Measuring Narrative-Induced Moral Reasoning Degradation in LLMs
Wanying Yu, Boyang Ma, Zhibo Eric Sun +2
Large language models are deployed in long-context, emotionally interactive environments like digital humans, AI companions, educational assistants, and counseling systems. Unlike…
"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…
A Measurement Study of Cryptographic Misuse in Embodied AI Mobile Applications
Junchao Li, Xuelei Wang, Yuhang Huang +5
Embodied AI (EAI) mobile applications are evolving from auxiliary user interfaces into active control-path components, directly linking mobile-side cryptographic security to cyber-…
MIRAGE: Stealthy Visual Prompt Injection for Vulnerability Detection in Web Agents
Xuelong Dai, Jianyu Ma, Boyang Ma +3
Multimodal Large Language Model (MLLM)-based web agents provide practical, high-precision solutions for visual browser automation; however, they inherently expand the attack surfac…
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…
What Breaks Embodied AI Security:LLM Vulnerabilities, CPS Flaws,or Something Else?
Boyang Ma, Hechuan Guo, Peizhuo Lv +5
Embodied AI systems (e.g., autonomous vehicles, service robots, and LLM-driven interactive agents) are rapidly transitioning from controlled environments to safety critical real-wo…
When Skills Lie: Hidden-Comment Injection in LLM Agents
Qianli Wang, Boyang Ma, Minghui Xu +1
LLM agents often rely on Skills to describe available tools and recommended procedures. We study a hidden-comment prompt injection risk in this documentation layer: when a Markdown…
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.…
Beyond Model Jailbreak: Systematic Dissection of the "Ten DeadlySins" in Embodied Intelligence
Yuhang Huang, Junchao Li, Boyang Ma +6
Embodied AI systems integrate language models with real world sensing, mobility, and cloud connected mobile apps. Yet while model jailbreaks have drawn significant attention, the b…
We Urgently Need Privilege Management in MCP: A Measurement of API Usage in MCP Ecosystems
Zhihao Li, Kun Li, Boyang Ma +3
The Model Context Protocol (MCP) has emerged as a widely adopted mechanism for connecting large language models to external tools and resources. While MCP promises seamless extensi…