AuditGPT: Auditing Smart Contracts with ChatGPT
To govern smart contracts running on Ethereum, multiple Ethereum Request for Comment (ERC) standards have been developed, each containing a set of rules to guide the behaviors of smart contracts. Violating the ERC rules could cause serious security issues and financial loss, signifying the importance of verifying smart contracts follow ERCs. Today's practices of such verification are to either manually audit each single contract or use expert-developed, limited-scope program-analysis tools, both of which are far from being effective in identifying ERC rule violations. This paper presents a tool named AuditGPT that leverages large language models (LLMs) to automatically and comprehensively verify ERC rules against smart contracts. To build AuditGPT, we first conduct an empirical study on 222 ERC rules specified in four popular ERCs to understand their content, their security impacts, their specification in natural language, and their implementation in Solidity. Guided by the study, we construct AuditGPT by separating the large, complex auditing process into small, manageable tasks and design prompts specialized for each ERC rule type to enhance LLMs' auditing performance. In the evaluation, AuditGPT successfully pinpoints 418 ERC rule violations and only reports 18 false positives, showcasing its effectiveness and accuracy. Moreover, AuditGPT beats an auditing service provided by security experts in effectiveness, accuracy, and cost, demonstrating its advancement over state-of-the-art smart-contract auditing practices.
Code (0)
등록된 구현이 없습니다.
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Evaluation of ChatGPT's Smart Contract Auditing Capabilities Based on Chain of Thought
Smart contracts, as a key component of blockchain technology, play a crucial role in ensuring the automation of transactions and adherence to protocol rules. However, smart contracts are susceptible to security vulnerabi…
Vulnerability DetectionFTSmartAudit: A Knowledge Distillation-Enhanced Framework for Automated Smart Contract Auditing Using Fine-Tuned LLMs
The rise of blockchain technologies has greatly accelerated the development and deployment of smart contracts. However, their inherent vulnerabilities and susceptibility to bugs have led to significant financial losses, …
Dataset GenerationKnowledge DistillationSC-Bench: A Large-Scale Dataset for Smart Contract Auditing
There is a huge demand to ensure the compliance of smart contracts listed on blockchain platforms to safety and economic standards. Today, manual efforts in the form of auditing are commonly used to achieve this goal. ML…
SymGPT: Auditing Smart Contracts via Combining Symbolic Execution with Large Language Models
To govern smart contracts running on Ethereum, multiple Ethereum Request for Comment (ERC) standards have been developed, each having a set of rules to guide the behaviors of smart contracts. Violating the ERC rules coul…
Natural Language UnderstandingRetrieval Augmented Generation Integrated Large Language Models in Smart Contract Vulnerability Detection
The rapid growth of Decentralized Finance (DeFi) has been accompanied by substantial financial losses due to smart contract vulnerabilities, underscoring the critical need for effective security auditing. With attacks be…
RAGRetrievalRetrieval-augmented GenerationVulnerability Detection