A survey on EOSIO systems security: vulnerability, attack, and mitigation

Ningyu HE, Haoyu WANG, Lei WU, Xiapu LUO, Yao GUO, Xiangqun CHEN

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Front. Comput. Sci. ›› 2025, Vol. 19 ›› Issue (6) : 196806. DOI: 10.1007/s11704-024-3278-y
Information Security
REVIEW ARTICLE

A survey on EOSIO systems security: vulnerability, attack, and mitigation

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Abstract

EOSIO, as a representative of blockchain 3.0 platforms, immediately follows in the footsteps of Bitcoin and Ethereum. It has raised the largest ever initial coin offering, and its market capitalization has reached up to $14.3 billion. Innovatively, EOSIO brings adopts lots of new features, like the delegated proof of stake consensus algorithm and updatable smart contracts. Not only these features lead to a prosperity of the decentralized application ecosystem, but they also inevitably introduce loopholes. For example, EOSBet, a famous gambling DApp, was attacked twice within a single month and lost more than $1 million. To the best of our knowledge, little work has surveyed the EOSIO from a security researcher’s perspective. To fill this gap, we firstly abstract the complicated EOSIO ecosystem into components following hierarchical relationships, upon which we delve deeper for root causes of all existing vulnerabilities. We also systematically study possible attacks and mitigations against these vulnerabilities, and summarize several best practices for developers, EOSIO official, and security researchers to shed light on future directions.

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Keywords

EOSIO / blockchain / smart contract

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Ningyu HE, Haoyu WANG, Lei WU, Xiapu LUO, Yao GUO, Xiangqun CHEN. A survey on EOSIO systems security: vulnerability, attack, and mitigation. Front. Comput. Sci., 2025, 19(6): 196806 https://doi.org/10.1007/s11704-024-3278-y

Ningyu He received his BS degree at Beijing University of Posts and Telecommunications, China in 2015. He is currently pursuing a PhD in Computer Software and Theory at Peking University, China. His current research interests include blockchain security and program analysis

Haoyu Wang is a professor in the School of Cyber Science and Engineering at Huazhong University of Science and Technology, China. He received his PhD degree in Computer Science from Peking University, China in 2016. His research covers a wide range of topics in Software Analysis, Privacy and Security, eCrime, Internet/System Measurement, and AI Security

Lei Wu is an associate professor at Zhejiang University and the Co-Founder of BlockSec. He obtained his PhD from North Carolina State University, USA in 2015 and primarily focuses his research on system security and blockchain security

Xiapu Luo is a professor in the Department of Computing, The Hong Kong Polytechnic University, China. His current research interests include Mobile and IoT Security and Privacy, Blockchain and Smart Contracts, Network Security and Privacy, and Software Engineering. His work appeared in top conferences and journals, and he has received eight best paper awards, including ACM SIGSOFT Distinguished Paper Award in ICSE’21, Best Paper Award in INFOCOM’18, etc

Yao Guo obtained his BS and MS degrees, both in Computer Science, from Peking University, China in 1997 and 2000, respectively. He received his PhD in Computer Engineering from University of Massachusetts at Amherst, USA in 2007. He currently is a professor in the Institute of Software of the School of Computer Science at Peking University and served as Vice Dean of the School of Computer Science. His general research interests include operating systems, mobile computing and applications, software security and software engineering

Xiangqun Chen obtained her BS and MS degrees from Peking University, China in 1983 and 1986, respectively. She is a professor in the School of Computer Science, and has served as the Party Secretary of School of Software and Microelectronics. She has published more than 70 research papers. Her research interests currently include operating systems, software engineering, and security

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Acknowledgements

The authors are grateful for the constructive advice received from the anonymous reviewers of this paper. The work described in this paper was partially funded by the National Key R&D Program of China (2021YFB2701000), the National Natural Science Foundation of China (Grants Nos. 62141208, 62172360, U21A20467), and the Hong Kong RGC Project (No. PolyU15224121).

Competing interests

The authors declare that they have no competing interests or financial conflicts to disclose.

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