A multi - agent framework for auditing Smart contracts

Abstract

Smart contracts power a vast array of blockchain applications, securing billions of dollars on decentralized finance, but their immutable nature turns every vulnerability into a permanent exploitable liability. Although automated security tools can efficiently detect many issues, their high false positive rates and lack of trust still require manual audits, which are costly and introduce deployment delays. In this paper, we present an end to end AI augmented auditing framework that leverages a multi-agent pipeline for comprehensive vulnerability detection and automated exploit generation. First, we review existing approaches such as static analysis, fuzzing, symbolic execution, formal verification, and machine learning methods, highlighting their strengths, limitations, and real world deployment experience. Building on this survey, we introduce a multi agent architecture composed of a Distributor Agent, an Attack Planner Agent, an Exploit Generator Agent, and an Audit Report Generator Agent. The pipeline ingests smart contract source code, documen-tation, and test suites to outline stepwise attack strategies and synthesize ready to compile Solidity exploit code. Exploits are compiled and validated in a containerized environment, enabling automated verification of attack effectiveness. We outline a validation strategy for future work, more specifically, applying the pipeline to capture the flag challenges and online bug bounty platforms, and we describe plans for prompt fine tuning, retrieval augmented generation, and formal verification integration to further enhance detection accuracy and exploit reliability. Our proposed framework promises a more comprehensive, scalable, and cost effective approach to smart contract security verification.