TY  - GEN
AV  - public
Y1  - 2024/02/06/
CY  - Lisbon, Portugal
TI  - Smart Contract and DeFi Security Tools:
Do They Meet the Needs of Practitioners?
EP  - 60
UR  - https://doi.org/10.1145/3597503.3623302
ID  - discovery10182359
N2  - The growth of the decentralized finance (DeFi) ecosystem built on blockchain technology and smart contracts has led to an increased demand for secure and reliable smart contract development. However, attacks targeting smart contracts are increasing, causing an estimated $6.45 billion in financial losses. Researchers have proposed various automated security tools to detect vulnerabilities, but their real-world impact remains uncertain.
In this paper, we aim to shed light on the effectiveness of automated security tools in identifying vulnerabilities that can lead to high-profile attacks, and their overall usage within the industry. Our comprehensive study encompasses an evaluation of five SoTA automated security tools, an analysis of 127 high-impact real-world attacks resulting in $2.3 billion in losses, and a survey of 49 developers and auditors working in leading DeFi protocols. Our findings reveal a stark reality: the tools could have prevented a mere 8% of the attacks in our dataset, amounting to $149 million out of the $2.3 billion in losses. Notably, all preventable attacks were related to reentrancy vulnerabilities. Furthermore, practitioners distinguish logic-related bugs and protocol layer vulnerabilities as significant threats that are not adequately addressed by existing security tools. Our results emphasize the need to develop specialized tools catering to the distinct demands and expectations of developers and auditors. Further, our study highlights the necessity for continuous advancements in security tools to effectively tackle the ever-evolving challenges confronting the DeFi ecosystem.
SP  - art no
N1  - © The Author(s), 2024. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. https://creativecommons.org/licenses/by/4.0/
A1  - Chaliasos, Stefanos
A1  - Charalambous, Marcos Antonios
A1  - Zhou, Liyi
A1  - Galanopoulou, Rafaila
A1  - Gervais, Arthur
A1  - Mitropoulos, Dimitris
A1  - Livshits, Benjamin
PB  - Association for Computing Machinery (ACM)
ER  -