28 citations · 29 across the 9 of their papers we have counts for
5 papers · 1 filter
ShadowProbe: Language-Extensible Detection of Hidden Algorithmic Complexity Vulnerabilities
Yuanmin Xie, Xiangfan Wu, Wenhao Wu +6
Algorithmic Complexity Vulnerabilities (ACVs) arise when adversarial inputs trigger worst-case execution behavior, causing severe performance degradation or Denial-of-Service condi…
MemPoison: Bypassing Selective Memory Mechanisms to Plant Backdoors in LLM Agents
Hongtao Wang, Se Yang, Yu Chen +1
Large language model (LLM) agents increasingly leverage long-term memory to support persistent and autonomous task execution. However, this capability also introduces a new attack…
Weaver: Fuzzing JavaScript Engines at the JavaScript-WebAssembly Boundary
Lingming Zhang, Binbin Zhao, Puzhuo Liu +4
The security of modern JavaScript (JS) engines is critical since they provide the primary defense mechanism for executing untrusted code on the web. The recent integration of WebAs…
MCPXKIT: The Unified Toolkit for Analyzing Model Context Protocol Security
Yongjian Guo, Puzhuo Liu, Wanlun Ma +5
The Model Context Protocol (MCP) has emerged as a universal standard that enables AI agents to seamlessly connect with external tools, significantly enhancing their functionality.…
Harnessing the Power of LLM to Support Binary Taint Analysis
Puzhuo Liu, Chengnian Sun, Yaowen Zheng +8
This paper proposes LATTE, the first static binary taint analysis that is powered by a large language model (LLM). LATTE is superior to the state of the art (e.g., Emtaint, Arbiter…