5 papers
TraceAegis: Securing LLM-Based Agents via Hierarchical and Behavioral Anomaly Detection
Jiahao Liu, Bonan Ruan, Xianglin Yang +5
LLM-based agents have demonstrated promising adaptability in real-world applications. However, these agents remain vulnerable to a wide range of attacks, such as tool poisoning and…
VULSOLVER: Vulnerability Detection via LLM-Driven Constraint Solving
Xiang Li, Yueci Su, Jiahao Liu +4
Traditional vulnerability detection methods rely heavily on predefined rule matching, which often fails to capture vulnerabilities accurately. With the rise of large language model…
Towards Scalable and Interpretable Mobile App Risk Analysis via Large Language Models
Yu Yang, Zhenyuan Li, Xiandong Ran +4
Mobile application marketplaces are responsible for vetting apps to identify and mitigate security risks. Current vetting processes are labor-intensive, relying on manual analysis…
A Large-Scale Evolvable Dataset for Model Context Protocol Ecosystem and Security Analysis
Zhiwei Lin, Bonan Ruan, Jiahao Liu +1
The Model Context Protocol (MCP) has recently emerged as a standardized interface for connecting language models with external tools and data. As the ecosystem rapidly expands, the…
ThreatPilot: Attack-Driven Threat Intelligence Extraction
Ming Xu, Hongtai Wang, Jiahao Liu +6
Efficient defense against dynamically evolving advanced persistent threats (APT) requires the structured threat intelligence feeds, such as techniques used. However, existing threa…