mlsanityData to 14 Oct 2026

Securing Smart Contract Languages with a Unified Agentic Framework for Vulnerability Repair in Solidity and Move

arXiv 2502.18515 ↗First posted 22 Feb 2025cs.CR cs.AI cs.MAcited by 1

On the map: LLM agents and tool use → Agent threats, guardrails and governance

Abstract (arXiv)

The rapid growth of the blockchain ecosystem and the increasing value locked in smart contracts necessitate robust security measures. While languages like Solidity and Move aim to improve smart contract security, vulnerabilities persist. This paper presents Smartify, a novel multi-agent framework leveraging Large Language Models (LLMs) to automatically detect and repair vulnerabilities in Solidity and Move smart contracts. Unlike traditional methods that rely solely on vast pre-training datasets, Smartify employs a team of specialized agents working on different specially fine-tuned LLMs to analyze code based on underlying programming concepts and language-specific security principles. We evaluated Smartify on a dataset for Solidity and a curated dataset for Move, demonstrating its effectiveness in fixing a wide range of vulnerabilities. Our results show that Smartify (Gemma2+codegemma) achieves state-of-the-art performance, surpassing existing LLMs and enhancing general-purpose models' capabilities, such as Llama 3.1. Notably, Smartify can incorporate language-specific knowledge, such as the nuances of Move, without requiring massive language-specific pre-training datasets. This work offers a detailed analysis of various LLMs' performance on smart contract repair, highlighting the strengths of our multi-agent approach and providing a blueprint for developing more secure and reliable decentralized applications in the growing blockchain landscape. We also provide a detailed recipe for extending this to other similar use cases.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 14 of its 36 references that are in the map. First posted on arXiv 22 Feb 2025.

Builds on

14 of 36 references.

References · 14

  1. 2023Code Llama: Open Foundation Models for Codecited by 2,139
  2. 2024DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligencecited by 1,181
  3. 2024StarCoder 2 and The Stack v2: The Next Generationcited by 502
  4. 2024CodeGemma: Open Code Models Based on Gemmacited by 150
  5. 2024OpenCoder: The Open Cookbook for Top-Tier Code Large Language Modelscited by 130
  6. 2019Slither: A Static Analysis Framework For Smart Contractscited by 89
  7. 2022Repair Is Nearly Generation: Multilingual Program Repair with LLMscited by 68
  8. 2019Manticore: A User-Friendly Symbolic Execution Framework for Binaries and Smart Contractscited by 37
  9. 2018ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detectioncited by 32
  10. 2021Fast and Reliable Formal Verification of Smart Contracts with the Move Provercited by 4
  11. 2024ContractTinker: LLM-Empowered Vulnerability Repair for Real-World Smart Contractscited by 4
  12. 2023Sui Lutris: A Blockchain Combining Broadcast and Consensuscited by 2
2 more
  1. 2025Do Automated Fixes Truly Mitigate Smart Contract Exploits?cited by 2
  2. 2022The Move Borrow Checkercited by 1

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Citing papers per year: 2025: 1.

1 paper.

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  1. 2024LLM-SmartAudit: Advanced Smart Contract Vulnerability Detection
  2. 2025LLM-BSCVM: An LLM-Based Blockchain Smart Contract Vulnerability Management Framework
  3. 2025SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection
  4. 2025ParaVul: A Parallel Large Language Model and Retrieval-Augmented Framework for Smart Contract Vulnerability Detection
  5. 2025Smart-LLaMA-DPO: Reinforced Large Language Model for Explainable Smart Contract Vulnerability Detection
  6. 2026CyberChainBench: Can AI Agents Secure Smart Contracts Against Real-World On-Chain Vulnerabilities?
  7. 2026SolAgent: A Specialized Multi-Agent Framework for Solidity Code Generation
  8. 2026Repository-Level Solidity Code Generation with Large Language Models: From Prompting to Fine-Tuning