14 citations · 35 across the 13 of their papers we have counts for
9 papers · 1 filter
Weaponizing the Exit: Input Privacy Leakage via Exit Routing Manipulation in Multi-Exit Networks
Yulong Tian, Lei Wang, Jincan Yang +4
Multi-exit networks improve inference efficiency by allowing inputs to terminate early at intermediate exits. We identify a privacy vulnerability in cloud deployments of these netw…
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…
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…
Revealing Adversarial Smart Contracts through Semantic Interpretation and Uncertainty Estimation
Yating Liu, Xing Su, Hao Wu +4
Adversarial smart contracts, mostly on EVM-compatible chains like Ethereum and BSC, are deployed as EVM bytecode to exploit vulnerable smart contracts for financial gain. Detecting…
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…
LEAP: TrustZone Based Developer-Friendly TEE for Intelligent Mobile Apps
Lizhi Sun, Shuocheng Wang, Hao Wu +5
ARM TrustZone is widely deployed on commercial-off-the-shelf mobile devices for secure execution. However, many Apps cannot enjoy this feature because it brings many constraints to…