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Over the last few years, there has been substantial research on automatedanalysis, testing, and debugging of Ethereum smart contracts. However, it isnot trivial to compare and reproduce that research. To address this, we presentan empirical evaluation of 9 state-of-the-art automated analysis tools usingtwo new datasets: i) a dataset of 69 annotated vulnerable smart contracts thatcan be used to evaluate the precision of analysis tools; and ii) a dataset withall the smart contracts in the Ethereum Blockchain that have Solidity sourcecode available on Etherscan (a total of 47,518 contracts). The datasets arepart of SmartBugs, a new extendable execution framework that we created tofacilitate the integration and comparison between multiple analysis tools andthe analysis of Ethereum smart contracts. We used SmartBugs to execute the 9automated analysis tools on the two datasets. In total, we ran 428,337 analysesthat took approximately 564 days and 3 hours, being the largest experimentalsetup to date both in the number of tools and in execution time. We found thatonly 42% of the vulnerabilities from our annotated dataset are detected by allthe tools, with the tool Mythril having the higher accuracy (27%). Whenconsidering the largest dataset, we observed that 97% of contracts are taggedas vulnerable, thus suggesting a considerable number of false positives.Indeed, only a small number of vulnerabilities (and of only two categories)were detected simultaneously by four or more tools.

Empirical Review of Automated Analysis Tools on 47,587 Ethereum Smart Contracts