Xiaoqi Li
4 indexed papers
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LibScan is an automated framework that detects eight categories of smart contract library misuse by combining LLM-based semantic reasoning with rule-based analysis, achieving 85.15% accuracy on real-world contracts.
LiquiLM is a novel framework that combines Large Language Models (LLMs) with a Dynamic Co-Attention Network (DCN) to effectively bridge the semantic gap between complex smart contract code and high-level liquidity flaw descriptions, achieving high accuracy in auditing DeFi systems.
The paper introduces PSR extsuperscript{2}, a novel static analysis framework that significantly improves the detection of atomicity violations in smart contracts by combining structural path searching with deep semantic reasoning.
NFTDELTA is a novel framework that uses multi-view learning on static code analysis to detect permission control vulnerabilities in NFT contracts with high accuracy.
Papers
NFTDELTA: Detecting Permission Control Vulnerabilities in NFT Contracts through Multi-View Learning
NFTDELTA is a novel framework that uses multi-view learning on static code analysis to detect permission control vulnerabilities in NFT contracts with high accuracy.