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20232026
most citedGPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysis

180 citations · 264 across the 13 of their papers we have counts for

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7 papers · 1 filter

cs.CR2026

Beyond Detection: Agentic Attack Synthesis and Simulation for Smart Contracts

Xianhao Zhang, Jing Sun, Zijian Zhang +4

Smart contract vulnerabilities pose severe financial risks, yet existing security tools largely stop at vulnerability detection, offering limited support for explaining whether rep…

cs.CR2026

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…

cs.CR2026

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…

cs.CR2026

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…

cs.CR2025

Casting a SPELL: Sentence Pairing Exploration for LLM Limitation-breaking

Yifan Huang, Xiaojun Jia, Wenbo Guo +4

Large language models (LLMs) have revolutionized software development through AI-assisted coding tools, enabling developers with limited programming expertise to create sophisticat…

cs.CR2024★ 19 cited

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,…

cs.CR2023★ 180 cited

GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysis

Yuqiang Sun, Daoyuan Wu, Yue Xue +5

Smart contracts are prone to various vulnerabilities, leading to substantial financial losses over time. Current analysis tools mainly target vulnerabilities with fixed control or…