Static Application Security Testing (SAST) Tools for Smart Contracts: How Far Are We?


연구 분야: Analysis



학회: Proceedings of the ACM on Software Engineering, Volume 1, Issue FSE


초록

In recent years, the importance of smart contract security has been heightened by the increasing number of attacks against them. To address this issue, a multitude of static application security testing (SAST) tools have been proposed for detecting vulnerabilities in smart contracts. However, objectively comparing these tools to determine their effectiveness remains challenging. Existing studies often fall short due to the taxonomies and benchmarks only covering a coarse and potentially outdated set of vulnerability types, which leads to evaluations that are not entirely comprehensive and may display bias. In this paper, we fill this gap by proposing an up-to-date and fine-grained taxonomy that includes 45 unique vulnerability types for smart contracts. Taking it as a baseline, we develop an extensive benchmark that covers 40 distinct types and includes a diverse range of code characteristics, vulnerability patterns, and application scenarios. Based on them, we evaluated 8 SAST tools using this benchmark, which comprises 788 smart contract files and 10,394 vulnerabilities. Our results reveal that the existing SAST tools fail to detect around 50% of vulnerabilities in our benchmark and suffer from high false positives, with precision not surpassing 10%. We also discover that by combining the results of multiple tools, the false negative rate can be reduced effectively, at the expense of flagging 36.77 percentage points more functions. Nevertheless, many vulnerabilities, especially those beyond Access Control and Reentrancy vulnerabilities, remain undetected. We finally highlight the valuable insights from our study, hoping to provide guidance on tool development, enhancement, evaluation, and selection for developers, researchers, and practitioners.


Author Profile
Sen Chen

Tianjin University Tianjin China

China
Author Profile
Yang Liu

Nanyang Technological University Singapore Singapore

Singapore
Author Profile
Haijun Wang

Xi'an Jiaotong University Xi'an China

China

📄 논문 정보

발행 연도 2024년
인용수 11
출판 국가 Singapore, China
사이트 ACM
좋아요 수 0

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