“Enhancing Smart Contract Security: Leveraging Generative AI for Vulnerability Remediation”

Abstract

The rapid proliferation of decentralized applications utilizing blockchain technology has emphasized the crucial role of smart contracts in ensuring secure and reliable transaction execution. Nonetheless, the inherent complexities related to smart contract development have resulted in various vulnerabilities, leading to significant financial losses and a deterioration of trust in the ecosystem. While traditional vulnerability detection techniques have made strides, the dynamic nature of smart contract vulnerabilities necessitates the exploration of novel, adaptive approaches. This paper proposes a generative AI-driven methodology for enhancing smart contract security by leveraging language models finetuned on curated datasets of solidity code, vulnerabilities, and remediation strategies. By harnessing the power of generative AI, our methodology effectively incorporates the identification of vulnerabilities and their subsequent resolution, offering aholistic approach to enhancing the security of smart contracts. While prior work has explored leveraging large language models for automatic code repair in other programming languages, this remains an open challenge for Solidity smart contracts. This study enhances the field of smart contract security by presenting an innovative resolution that merges AI methodologies with blockchain technology, with the goal of mitigating risks and fostering trust in decentralized systems.