6 papers
Attention Distance: A Novel Metric for Directed Fuzzing with Large Language Models
Wang Bin, Ao Yang, Kedan Li +5
In the domain of software security testing, Directed Grey-Box Fuzzing (DGF) has garnered widespread attention for its efficient target localization and excellent detection performa…
Argus: A Multi-Agent Sensitive Information Leakage Detection Framework Based on Hierarchical Reference Relationships
Bin Wang, Hui Li, Liyang Zhang +5
Sensitive information leakage in code repositories has emerged as a critical security challenge. Traditional detection methods that rely on regular expressions, fingerprint feature…
RefleXGen:The unexamined code is not worth using
Bin Wang, Hui Li, AoFan Liu +7
Security in code generation remains a pivotal challenge when applying large language models (LLMs). This paper introduces RefleXGen, an innovative method that significantly enhance…
MCPGuard : Automatically Detecting Vulnerabilities in MCP Servers
Bin Wang, Zexin Liu, Hao Yu +6
The Model Context Protocol (MCP) has emerged as a standardized interface enabling seamless integration between Large Language Models (LLMs) and external data sources and tools. Whi…
RA-Gen: A Controllable Code Generation Framework Using ReAct for Multi-Agent Task Execution
Aofan Liu, Haoxuan Li, Bin Wang +2
Code generation models based on large language models (LLMs) have gained wide adoption, but challenges remain in ensuring safety, accuracy, and controllability, especially for comp…
PiCo: Jailbreaking Multimodal Large Language Models via Pictorial Code Contextualization
Aofan Liu, Lulu Tang, Ting Pan +3
Multimodal Large Language Models (MLLMs), which integrate vision and other modalities into Large Language Models (LLMs), significantly enhance AI capabilities but also introduce ne…