Optimization of Smart Contract Reentrancy Vulnerabilities Based on Static Analysis

Abstract

A smart contract is a program deployed on a blockchain network and becomes immutable once deployed. Reentrancy bugs are among the most significant vulnerabilities in blockchain technology. Numerous approaches have been proposed to detect and analyze them. However, minimizing reentrancy errors in smart contracts remains a challenge. The aim of this paper is to optimize the handling of reentrancy bugs in smart contracts across different versions of Solidity. It also proposes a new method for syntactic and lexical code detection. Our approach is based on static analysis, and the tool can detect different versions of smart contract code. We used regex to identify external calls in the contract and Control Flow Graph (CFG) to identify the components of the code. A detection algorithm was developed to identify reentrancy vulnerabilities. This approach enhances contract reliability and reduces risk prior to deployment. Our method has been evaluated using True Positive Rate (TPR) and False Positive Rate (FPR) metrics. We tested it on the SmartBugs benchmark suite and contracts from Etherscan. The contracts analyzed include two solidity versions: 0.4.x and 0.8.x. Thanks to the integration of multiple tools, our solution supports testing across different solidity versions.