MANDO-GURU: vulnerability detection for smart contract source code by heterogeneous graph embeddings

• Main Authors: NGUYEN, Huu Hoang, NGUYEN, Nhat Minh, DOAN, Hong-Phuc, AHMADI, Zahrai, DOAN, Thanh Nam, JIANG, Lingxiao
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Heterogeneous graphs; Graph neural networks; Vulnerability detection; Smart contracts; Ethereum blockchain; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/7644; https://ink.library.smu.edu.sg/context/sis_research/article/8647/viewcontent/fse22mandoDemo.pdf
• Institution: Singapore Management University

Smart contracts are increasingly used with blockchain systems for high-value applications. It is highly desired to ensure the quality of smart contract source code before they are deployed. This paper proposes a new deep learning-based tool, MANDO-GURU, that aims to accurately detect vulnerabilities...