5 citations · 5 across the 5 of their papers we have counts for
6 papers · 1 filter
The Guard That Cried Wolf: How Scary Words Make Agent Guardrails Refuse Legitimate Actions
Yingjie Zhang, Yuanbo Xie, Kai Chen
Agent guardrails are checks that approve or refuse each action before an LLM executes it. Sometimes they refuse requests that are genuinely safe. This over-safety blocks deployment…
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…