AuditAI: Automating and Facilitating the Audit of Smart Contracts with Contextual Reports Generated by AI

• Lívia Carrera UFPA http://orcid.org/0000-0001-5329-8080
• Ramón Cordeiro TU Delft
• Antônio Abelém UFPA https://orcid.org/0000-0003-4085-6674

DOI: https://doi.org/10.5753/wblockchain.2025.9134

Abstract

Smart contract security remains a major challenge in blockchain development, often limited by manual audits and static analysis tools.This paper introduces AuditAI, a platform that combines the Slither static analyzer with Large Language Models (LLMs) served via Groq Artificial Intelligence (AI) to detect vulnerabilities and generate contextualized, customizable audit reports. By merging formal analysis with natural language interpretation, AuditAI enhances the clarity and accessibility of security assessments. Preliminary results indicate improvements, in both the efficiency and interpretability of smart contract audits, while acknowledging the persistent challenges in automated vulnerability detection.

Keywords: Blockchain Security, Smart Contract Auditing, Blockchain, Smart Contract Security, Slither, Generative Artificial Intelligence, Large Language Models (LLMs), Groq AI, Static Analysis, Contextualized Reports, Audit Automation, Solidity, Vulnerability Detection

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