37 citations · 56 across the 8 of their papers we have counts for
5 papers · 1 filter
Knowledge Over Parameters: Evolving Smart Contract Vulnerability Detection
Yuqiang Sun, Han Liu, Ying Li +4
Smart contract vulnerabilities are predominantly logic bugs whose detection requires structured, step-by-step procedural knowledge of attack patterns and contract semantics. Existi…
TrajAD: Trajectory Anomaly Detection for Trustworthy LLM Agents
Yibing Liu, Chong Zhang, Zhongyi Han +5
We address the problem of runtime trajectory anomaly detection, a critical capability for enabling trustworthy LLM agents. Current safety measures predominantly focus on static inp…
LogicScan: An LLM-driven Framework for Detecting Business Logic Vulnerabilities in Smart Contracts
Jiaqi Gao, Zijian Zhang, Yuqiang Sun +5
Business logic vulnerabilities have become one of the most damaging yet least understood classes of smart contract vulnerabilities. Unlike traditional bugs such as reentrancy or ar…
Do Fine-Tuned LLMs Understand Vulnerabilities? An Investigation into the Semantic Trap
Feiyang Huang, Yuqiang Sun, Fan Zhang +3
Large Language Models (LLMs) have shown promising performance in software vulnerability detection, particularly after domain-specific Supervised Fine-Tuning (SFT). However, it rema…
LLM4Vuln: A Unified Evaluation Framework for Decoupling and Enhancing LLMs' Vulnerability Reasoning
Yuqiang Sun, Daoyuan Wu, Yue Xue +5
Large language models (LLMs) have demonstrated significant potential in various tasks, including those requiring human-level intelligence, such as vulnerability detection. However,…