🤖 AI Summary
Smart contracts’ reliance on external data introduces significant security and reliability risks, yet systematic empirical studies remain scarce. To address this gap, we conduct the first large-scale statistical analysis of 9,356 real-world smart contracts, integrating abstract syntax tree parsing, keyword matching, manual annotation, and mining of professional security audit reports to construct the first structured database of external dependencies. We propose a reproducible framework for identifying and classifying such dependencies, revealing a statistically significant positive correlation between contract complexity and external dependency intensity. Our analysis uncovers 249 vulnerabilities directly attributable to external data handling—constituting 9% of all reported vulnerabilities in the audited datasets. These findings provide critical empirical evidence and foundational infrastructure to support secure smart contract development, formal verification, and security auditing practices.
📝 Abstract
Smart contracts with external data are crucial for functionality but pose security and reliability concerns. Statistical and quantitative studies on this interaction are scarce. To address this gap, we analyzed 10,500 smart contracts, retaining 9,356 valid ones after excluding outdated or erroneous ones.We employed code parsing to transform contract code into abstract syntax trees and identified keywords associated with external data dependencies. We conducted a quantitative analysis by comparing these keywords to a reference list. We manually classified the 9,356 valid smart contracts to ascertain their application domains and typical interaction methods with external data. Additionally, we created a database with this data to facilitate research on smart contract dependencies. Moreover, we reviewed over 3,600 security audit reports, manually identifying 249 (approximately 9%) related to external data interactions and categorized their dependencies. We explored the correlation between smart contract complexity and external data dependency to provide insights for their design and auditing processes. These studies aim to enhance the security and reliability of smart contracts and offer practical guidance to developers and auditors.