Vulnerability Analysis of Ethereum Smart Contracts Using Automated Static Analysis with Slither
Keywords:
Blockchain security, Ethereum, Reetrancy, Smart contract, Static analysisAbstract
(1) Background: Smart contracts on the Ethereum blockchain are immutable, meaning any security flaw can lead to catastrophic financial losses. Vulnerabilities such as Reentrancy and other logic flaws remain a serious threat to decentralized applications. (2) Purpose of the Study: This research aims to analyze security vulnerabilities in open Ethereum smart contracts through automated batch processing using the Slither static analysis tool integrated into a web-based auditing framework. (3) Methods: The research employed an experimental approach by auditing 10 open smart contracts via the Etherscan API. The evaluation mapped detected vulnerabilities to standard severity levels (High, Medium, Low, Informational) and quantified overall contract security using a structured Risk Score algorithm. (4) Results: The automated static analysis pipeline achieved a 100% compilation and scanning success rate across all evaluated contracts, yielding an average risk score of 44 out of 100. The findings indicate a prevalence of functional, code-naming, and access-control issues, alongside critical Reentrancy logic flaws in specific contracts. (5) Conclusions: Automated static analysis significantly accelerates the efficient identification of critical smart contract vulnerabilities before mainnet deployment. Future research should combine static analysis with dynamic testing techniques, such as fuzzing, to achieve more comprehensive security audits.
References
Di Angelo, M., & Salzer, G. (2019). A Survey of Tools for Analyzing Ethereum Smart Contracts. 2019 IEEE International Conference on Decentralized Applications and Infrastructures (DAPPS), 69-78. 10.1109/DAPPCON.2019.00018.
Durieux, T., Ferreira, J. F., Abreu, R., & Cruz, P. (2020). Empirical Review of Automated Analysis Tools for Smart Contracts. IEEE Transactions on Software Engineering, 46(12), 1308-1320. https://doi.org/10.48550/arXiv.1910.10601.
Feist, J., Grieco, G., & Groce, A. (2019). Slither: A Static Analysis Framework for Smart Contracts. 2019 IEEE/ACM 2nd International Workshop on Emerging Trends in Software Engineering for Blockchain (WETSEB), 8-15. https://doi.org/10.1109/WETSEB.2019.00008.
Ghaleb, A., & Pattabiraman, K. (2022). How Effective Are Smart Contract Analysis Tools? Evaluated on 22,864 Smart Contracts. IEEE Transactions on Reliability, 71(1), 336-351. https://doi.org/10.48550/arXiv.2005.11613.
Luu, L., Chu, D.-H., Olickel, H., Saxena, P., & Hobor, A. (2016). Making Smart Contracts Smarter. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, 254-269. https://doi.org/10.1145/2976749.2978309.
Zheng, Z., Xie, S., Dai, H., Chen, X., & Wang, H. (2017). An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends. 2017 IEEE International Congress on Big Data (BigData Congress), 557-564. https://doi.org/10.1109/BigDataCongress.2017.85.
Kushwaha, S. S., Joshi, S., Singh, D., Kaur, M., & Lee, H. N. (2022). Systematic review of security vulnerabilities in Ethereum smart contracts. IEEE Access, 10, 6605-6621. https://doi.org/10.1109/ACCESS.2021.3140091.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Rahmat Rifai Arsandi
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
