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A Learning Framework for Smart Contract Vulnerability and Root Cause Detection
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DOI：10.1016/j.bcra.2026.100502.png)
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Abstract
En 中文
Smart contracts enable decentralized applications across domains such as finance, logistics, and healthcare, but their immutable nature and complex execution logic make them highly susceptible to vulnerabilities, including reentrancy, integer overflows, and access control flaws. These weaknesses can lead to severe financial and operational losses. Traditional static or rule-based detection tools lack scalability and adaptability, while existing deep learning models often struggle with limited data, poor generalization, and the absence of actionable mitigation guidance.
Keywords:
Smart contracts
Vulnerability
Security
Large Language Model
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