Static Application Security Testing (SAST) Tools for Smart Contracts: How Far Are We?
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Abstract (arXiv)
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 Existing studies often fall short due to the taxonomies and benchmarks only covering a coarse and potentially outdated set of vulnerability types, which leads to evaluations that are not entirely comprehensive and may display bias.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.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Apr 2024.
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Citing papers per year: 2025: 2; 2026: 3.
5 papers.
- 2025LISA Technical Report: An Agentic Framework for Smart Contract Auditingcited by 2
- 2026Knowdit: Agentic Smart Contract Vulnerability Detection with Auditing Knowledge Summarizationcited by 1
- 2025Software Vulnerability Management in the Era of Artificial Intelligence: An Industry Perspectivecited by 0
- 2026SoK: AI Secure Code Generation: Progress, Pitfalls, and Paths Forwardcited by 0
- 2026RAGas: Retrieval-Augmented Gas Optimization for Smart Contracts with Continuous Knowledge Integrationcited by 0
- 2026RAGas: Retrieval-Augmented Gas Optimization for Smart Contracts with Continuous Knowledge Integration16 Aug 2026
- 2026SoK: AI Secure Code Generation: Progress, Pitfalls, and Paths Forward23 Jun 2026
- 2026Knowdit: Agentic Smart Contract Vulnerability Detection with Auditing Knowledge Summarization27 Mar 2026
- 2025Software Vulnerability Management in the Era of Artificial Intelligence: An Industry Perspective20 Dec 2025
- 2025LISA Technical Report: An Agentic Framework for Smart Contract Auditing29 Sep 2025