A Comprehensive Taxonomy of DeFi Attack Patterns: 50 Vectors from 824 Incidents (2017-2026)
We present the first comprehensive taxonomy of 50 distinct DeFi attack vectors, empirically validated against 824 confirmed incidents spanning 2017-2026. Our classification achieves 97.6% coverage (804/824 cases categorized) compared to 58% for the best prior taxonomy. Each pattern includes a canonical real-world example, detection methodology, and Slither detection rule. We find that 8 patterns account for 76% of all losses, with flash loan + oracle manipulation alone responsible for 24% of cases and 60% of total losses ($6B+). The taxonomy reveals that 12 patterns (24%) lack Slither rules entirely, and 18 patterns (36%) require business-logic understanding beyond static analysis. We release the complete taxonomy, detection rules, and an open-source 50-rule DeFi scanner.
Authors
- Shiqiang Chen (ORCID: https://orcid.org/0000-0001-8804-6094)
Institutions
- Chinese Academy of Sciences (CN)
- Institute of Information Engineering (CN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-07-17
- DOI
- https://doi.org/10.5281/zenodo.21405849
- Primary Topic
- Financial Distress and Bankruptcy Prediction
- Type
- preprint