Vulnerability Scanners for Ethereum Smart Contracts: A Large-Scale Study
Christoph Sendner, Lukas Petzi, Jasper Stang, Alexandra Dmitrienko

TL;DR
This large-scale study evaluates 17 Ethereum smart contract vulnerability scanners, revealing significant gaps between their effectiveness and the actual vulnerabilities, and highlighting the need for improved security tools.
Contribution
The paper provides a comprehensive evaluation of existing vulnerability scanners against extensive datasets, exposing their limitations and the persistent challenge of detecting smart contract vulnerabilities.
Findings
All tested tools perform poorly against ground truth datasets.
Significant discrepancies exist among different vulnerability scanners.
Current tools are insufficient for effective smart contract vulnerability detection.
Abstract
Ethereum smart contracts, which are autonomous decentralized applications on the blockchain that manage assets often exceeding millions of dollars, have become primary targets for cyberattacks. In 2023 alone, such vulnerabilities led to substantial financial losses exceeding a billion of US dollars. To counter these threats, various tools have been developed by academic and commercial entities to detect and mitigate vulnerabilities in smart contracts. Our study investigates the gap between the effectiveness of existing security scanners and the vulnerabilities that still persist in practice. We compiled four distinct datasets for this analysis. The first dataset comprises 77,219 source codes extracted directly from the blockchain, while the second includes over 4 million bytecodes obtained from Ethereum Mainnet and testnets. The other two datasets consist of nearly 14,000 manually…
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Taxonomy
TopicsBlockchain Technology Applications and Security · Cryptography and Data Security · Advanced Malware Detection Techniques
