1 citations · 2 across the 8 of their papers we have counts for
9 papers
Usability as a Weapon: Attacking the Safety of LLM-Based Code Generation via Usability Requirements
Yue Li, Xiao Li, Hao Wu +5
Large Language Models (LLMs) are increasingly used for automated software development, making their ability to preserve secure coding practices critical. In practice, however, many…
CoTDeceptor:Adversarial Code Obfuscation Against CoT-Enhanced LLM Code Agents
Haoyang Li, Mingjin Li, Jinxin Zuo +5
LLM-based code agents(e.g., ChatGPT Codex) are increasingly deployed as detector for code review and security auditing tasks. Although CoT-enhanced LLM vulnerability detectors are…
A Systematic Study of Code Obfuscation Against LLM-based Vulnerability Detection
Xiao Li, Yue Li, Hao Wu +4
As large language models (LLMs) are increasingly adopted for code vulnerability detection, their reliability and robustness across diverse vulnerability types have become a pressin…
ConneX: Automatically Resolving Transaction Opacity of Cross-Chain Bridges for Security Analysis
Hanzhong Liang, Yue Duan, Xing Su +5
As the Web3 ecosystem evolves toward a multi-chain architecture, cross-chain bridges have become critical infrastructure for enabling interoperability between diverse blockchain ne…
MedFoundationHub: A Lightweight and Secure Toolkit for Deploying Medical Vision Language Foundation Models
Xiao Li, Yanfan Zhu, Ruining Deng +6
Recent advances in medical vision-language models (VLMs) open up remarkable opportunities for clinical applications such as automated report generation, copilots for physicians, an…
When LLMs Copy to Think: Uncovering Copy-Guided Attacks in Reasoning LLMs
Yue Li, Xiao Li, Hao Wu +4
Large Language Models (LLMs) have become integral to automated code analysis, enabling tasks such as vulnerability detection and code comprehension. However, their integration intr…
Everything You Wanted to Know About LLM-based Vulnerability Detection But Were Afraid to Ask
Yue Li, Xiao Li, Hao Wu +5
Large Language Models are a promising tool for automated vulnerability detection, thanks to their success in code generation and repair. However, despite widespread adoption, a cri…
If LLMs Would Just Look: Simple Line-by-line Checking Improves Vulnerability Localization
Yue Li, Xiao Li, Hao Wu +5
The rapid expansion of software systems and the growing number of reported vulnerabilities have emphasized the importance of accurately identifying vulnerable code segments. Tradit…
Reversing the asymmetry in data exfiltration
David Skillicorn, Xiao Li, Karen Chen
Preventing data exfiltration from computer systems typically depends on perimeter defences, but these are becoming increasingly fragile. Instead we suggest an approach in which eac…