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Slither: A Static Analysis Framework for Smart Contracts
Open accessAbstract
This paper describes Slither, a static analysis framework designed to provide rich information about Ethereum smart contracts. It works by converting Solidity smart contracts into an intermediate representation called SlithIR. SlithIR uses Static Single Assignment (SSA) form and a reduced instruction set to ease implementation of analyses while preserving semantic information that would be lost in transforming Solidity to bytecode. Slither allows for the application of commonly used program analysis techniques like dataflow and taint tracking. Our framework has four main use cases: (1) automated detection of vulnerabilities, (2) automated detection of code optimization opportunities, (3) improvement of the user's understanding of the contracts, and (4) assistance with code review. In this paper, we present an overview of Slither, detail the design of its intermediate representation, and evaluate its capabilities on real-world contracts. We show that Slither's bug detection is fast, accurate, and outperforms other static analysis tools at finding issues in Ethereum smart contracts in terms of speed, robustness, and balance of detection and false positives. We compared tools using a large dataset of smart contracts and manually reviewed results for 1000 of the most used contracts.
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Cited by
Empirical review of automated analysis tools on 47,587 Ethereum smart contracts
Durieux, T., Ferreira, J. F., Abreu, R., & Cruz, P. (2020) · Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering · doi:10.1145/3377811.3380364 · Cited by 409
Smart Contract: Attacks and Protections
Sayeed, S., Marco-Gisbert, H., & Caira, T. (2020) · IEEE Access · doi:10.1109/access.2020.2970495 · Cited by 322
Rethinking Smart Contract Fuzzing: Fuzzing With Invocation Ordering and Important Branch Revisiting
Liu, Z., Qian, P., Yang, J., Liu, L., Xu, X., He, Q., & Zhang, X. (2023) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2023.3237370 · Cited by 138
Do not rug on me: Leveraging machine learning techniques for automated scam detection
Mazorra, B., Adan, V., & Daza, V. (2022) · Mathematics · doi:10.3390/math10060949 · Cited by 64
Advanced Smart Contract Vulnerability Detection via LLM-Powered Multi-Agent Systems
Wei, Z., Sun, J., Sun, Y., Liu, Y., Wu, D., Zhang, Z., Zhang, X., Li, M., Liu, Y., Li, C., et al. (2025) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2025.3597319 · Cited by 31
Metadata
- Authors
- Feist, J., Grieco, G., & Groce, A.
- Venue
- 2019 IEEE/ACM 2nd International Workshop on Emerging Trends in Software Engineering for Blockchain (WETSEB)
- Publisher
- IEEE
- Published
- 2019-05
- Pages
- 8-15
- OpenAlex
- W2970809537
- Cited by
- 872
- References
- 0
- FWCI
- 33.57
- Type
- conference paper
- Language
- en
- Open access
- green
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- 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). https://doi.org/10.1109/wetseb.2019.00008
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