collaborators

7 papers

cs.CR2026

Cheap to Hypothesize, Costly to Verify: The Defense Surface of Agentic Vulnerability Discovery

Kaikai Zhang, Zihan Zhang, Yuchong Xie +4

Autonomous LLM agents turn vulnerability discovery into a repository-scale search: they generate many vulnerability hypotheses but can verify only a subset under a finite budget. W…

cs.CR2026

Similarity Is Not Validity: Defending LLM Semantic Caches Against Poisoning

Zihan Zhang, Shuangjie Yao, Zesen Liu +8

Semantic caches reduce LLM serving costs by reusing previously generated answers for semantically similar queries. However, retrieval is based solely on embedding similarity betwee…

cs.CR2026

Rewriting the Response Path: Silent Tampering and Provider-Signed Defense in BYOK LLM Agents

Mingyu Luo, Zihan Zhang, Zesen Liu +7

LLM agents convert model outputs into consequential actions, including communications, code changes, and financial transactions. Developers often trust evidence such as test result…

cs.CR2026

From Similarity to Vulnerability: Key Collision Attack on LLM Semantic Caching

Zhixiang Zhang, Zesen Liu, Yuchong Xie +2

Semantic caching has emerged as a pivotal technique for scaling LLM applications, widely adopted by major providers including AWS and Microsoft. By utilizing semantic embedding vec…

cs.CR2025

QueryIPI: Query-agnostic Indirect Prompt Injection on Coding Agents

Yuchong Xie, Zesen Liu, Mingyu Luo +7

Modern coding agents integrated into IDEs orchestrate powerful tools and high-privilege system access, creating a high-stakes attack surface. Prior work on Indirect Prompt Injectio…

cs.CR2025

When Compression Becomes an Attack Surface: Black-Box Attacks on Prompt-Compressed LLM Agents

Zesen Liu, Zhixiang Zhang, Yuchong Xie +1

Prompt compression is increasingly deployed in LLM agents to reduce latency and cost, but it also determines what the backend LLM ultimately sees. We show that, when trusted and un…

cs.CR2025

Red-Teaming Coding Agents from a Tool-Invocation Perspective: An Empirical Security Assessment

Yuchong Xie, Mingyu Luo, Zesen Liu +7

Coding agents powered by large language models are becoming central modules of modern IDEs, helping users perform complex tasks by invoking tools. While powerful, tool invocation o…