9 papers
Description-Code Inconsistency in Real-world MCP Servers: Measurement, Detection, and Security Implications
Yutao Shi, Xiaohan Zhang, Xiangjing Zhang +5
The Model Context Protocol (MCP) has emerged as a critical standard empowering Large Language Models (LLMs) to utilize external tools. In this ecosystem, LLMs rely on natural langu…
Broken Memories: Detecting and Mitigating Memorization in Diffusion Models with Degraded Generations
Yuanmin Huang, Mi Zhang, Chen Chen +4
While diffusion models excel at generating high-quality images, their tendency to memorize training data poses significant privacy and copyright risks. In this work, we for the fir…
A First Measurement Study on Authentication Security in Real-World Remote MCP Servers
Huijun Zhou, Xiaohan Zhang, Haozhe Zhang +3
The Model Context Protocol (MCP) is emerging as a common interface connecting large language models (LLMs) with external services. Remote deployments are becoming increasingly impo…
From Anchors to Supervision: Memory-Graph Guided Corpus-Free Unlearning for Large Language Models
Wenxuan Li, Zhenfei Zhang, Mi Zhang +4
Large language models (LLMs) may memorize sensitive or copyrighted content, raising significant privacy and legal concerns. While machine unlearning has emerged as a potential reme…
SafeRoPE: Risk-specific Head-wise Embedding Rotation for Safe Generation in Rectified Flow Transformers
Xiang Yang, Feifei Li, Mi Zhang +3
Recent Text-to-Image (T2I) models based on rectified-flow transformers (e.g., SD3, FLUX) achieve high generative fidelity but remain vulnerable to unsafe semantics, especially when…
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…