SmartLLMSentry: A Comprehensive LLM Based Smart Contract Vulnerability Detection Framework
Smart contracts are essential for managing digital assets in blockchain networks, highlighting the need for effective security measures. This paper introduces SmartLLMSentry, a novel framework that leverages large language models (LLMs), specifically ChatGPT with in-context training, to advance smar...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
İzmir Akademi Derneği
2024-12-01
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| Series: | Journal of Metaverse |
| Subjects: | |
| Online Access: | https://dergipark.org.tr/en/download/article-file/3951976 |
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| Summary: | Smart contracts are essential for managing digital assets in blockchain networks, highlighting the need for effective security measures. This paper introduces SmartLLMSentry, a novel framework that leverages large language models (LLMs), specifically ChatGPT with in-context training, to advance smart contract vulnerability detection. Traditional rule-based frameworks have limitations in integrating new detection rules efficiently. In contrast, SmartLLMSentry utilizes LLMs to streamline this process. We created a specialized dataset of five randomly selected vulnerabilities for model training and evaluation. Our results show an exact match accuracy of 91.1% with sufficient data, although GPT-4 demonstrated reduced performance compared to GPT-3 in rule generation. This study illustrates that SmartLLMSentry significantly enhances the speed and accuracy of vulnerability detection through LLM-driven rule integration, offering a new approach to improving Blockchain security and addressing previously underexplored vulnerabilities in smart contracts. |
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| ISSN: | 2792-0232 |