5 papers
What If Prompt Injection Never Left? Rethinking Agent Security through Cross-Session Stored Prompt Injection
Yuanbo Xie, Wenlei Zhu, Tianyun Liu +5
Modern agentic systems fundamentally reshape the security boundary of LLMs by introducing persistent system state including memories, filesystems, tools, and other long-lived conte…
Detecting RAG Extraction Attack via Dual-Path Runtime Integrity Game
Yuanbo Xie, Yingjie Zhang, Yulin Li +5
Retrieval-Augmented Generation (RAG) systems augment large language models with external knowledge, yet introduce a critical security vulnerability: RAG Knowledge Base Leakage, whe…
Bleeding Pathways: Vanishing Discriminability in LLM Hidden States Fuels Jailbreak Attacks
Yingjie Zhang, Tong Liu, Zhe Zhao +2
LLMs remain vulnerable to jailbreak attacks that exploit adversarial prompts to circumvent safety measures. Current safety fine-tuning approaches face two critical limitations. Fir…
Global Challenge for Safe and Secure LLMs Track 1
Xiaojun Jia, Yihao Huang, Yang Liu +27
This paper introduces the Global Challenge for Safe and Secure Large Language Models (LLMs), a pioneering initiative organized by AI Singapore (AISG) and the CyberSG R&D Programme…
Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction
Tong Liu, Yingjie Zhang, Zhe Zhao +3
In recent years, large language models (LLMs) have demonstrated notable success across various tasks, but the trustworthiness of LLMs is still an open problem. One specific threat…