6 papers
Security Assessment of DeepSeek Harness with A.I.G: Evaluating Resistance to Indirect Prompt Injection
Zonghao Ying, Xiangfan Wu, Huiyu Wu +4
We assess indirect prompt injection in DeepSeek Harness (DSH), using AI-Infra-Guard (A.I.G) to construct tests, deliver controlled taint, execute DSH, collect traces, and judge out…
Ventor-QTest: Threat-Model-Driven Verification of Vendor-Hosted LLM APIs
Xiangfan Wu, Zonghao Ying, Huiyu Wu +4
As large language models become increasingly widespread, third-party providers that deploy open-weight models have become an important part of the ecosystem. Auditing the quality o…
SkillJack: Persistent Skill Backdoors in Self-Evolving Agents
Zonghao Ying, Xiangfan Wu, Huiyu Wu +4
Self-evolving agents increasingly convert interaction histories into reusable skills that persist beyond individual tasks. While prior work studies memory and retrieval poisoning,…
Securing the AI Agent: A Unified Framework for Multi-Layer Agent Red Teaming
Yong Yang, Xing Zheng, Huiyu Wu +7
The fast growth of open-source AI infrastructure, from model serving engines and agent platforms to the Model Context Protocol (MCP) ecosystem and the language models themselves, h…
Is Your Prompt Poisoning Code? Defect Induction Rates and Security Mitigation Strategies
Bin Wang, YiLu Zhong, MiDi Wan +4
Large language models (LLMs) have become indispensable for automated code generation, yet the quality and security of their outputs remain a critical concern. Existing studies pred…
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…