WANA: Symbolic Execution of Wasm Bytecode for Extensible Smart Contract Vulnerability Detection

被引:12
|
作者
Jiang, Bo [1 ]
Chen, Yifei [1 ]
Wang, Dong [1 ]
Ashraf, Imran [2 ]
Chan, W. K. [2 ]
机构
[1] Beihang Univ, Sch Comp Sci & Engn, Beijing, Peoples R China
[2] City Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China
基金
国家重点研发计划;
关键词
WASM bytecode; Symbolic Execution; Smart Contract; Vulnerability Detection;
D O I
10.1109/QRS54544.2021.00102
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Many popular blockchain platforms support smart contracts for building decentralized applications. However, the vulnerabilities within smart contracts have demonstrated to lead to serious financial loss to their end users. In particular, the smart contracts on EOSIO smart contract platform have resulted in the loss of around 380K EOS tokens, which was around 1.9 million worth of USD at the time of attack. The EOSIO smart contract platform is based on the Wasm VM, which is also the underlying system supporting other smart contract platforms as well as Web application. In this work, we present WANA, an extensible smart contract vulnerability detection tool based on the symbolic execution for Wasm bytecode. WANA proposes a set of algorithms to detect the vulnerabilities in EOSIO smart contracts based on Wasm bytecode analysis. Our experimental analysis shows that WANA can effectively and efficiently detect vulnerabilities in EOSIO smart contracts. Furthermore, our case study also demonstrates that WANA can be extended to effectively detect vulnerabilities in Ethereum smart contracts.
引用
收藏
页码:926 / 937
页数:12
相关论文
共 50 条
  • [21] Smart Contract Vulnerability Detection Using Code Representation Fusion
    Wang, Ben
    Chu, Hanting
    Zhang, Pengcheng
    Dong, Hai
    2021 28TH ASIA-PACIFIC SOFTWARE ENGINEERING CONFERENCE (APSEC 2021), 2021, : 564 - 565
  • [22] Smart Contract Vulnerability Detection Using Graph Neural Networks
    Zhuang, Yuan
    Liu, Zhenguang
    Qian, Peng
    Liu, Qi
    Wang, Xiang
    He, Qinming
    PROCEEDINGS OF THE TWENTY-NINTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2020, : 3283 - 3290
  • [23] Smart Contract Timestamp Vulnerability Detection Based on Code Homogeneity
    Wang, Weizhi
    Xia, Lei
    Zhang, Zhuo
    Meng, Xiankai
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2024, E107D (10) : 1362 - 1366
  • [24] QuadraCode AI: Smart Contract Vulnerability Detection with Multimodal Representation
    Upadhya, Jiblal
    Upadhyay, Kritagya
    Sainju, Arpan
    Poudel, Samir
    Hasan, Md Nahid
    Poudel, Khem
    Ranganathan, Jaishree
    2024 33RD INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATIONS AND NETWORKS, ICCCN 2024, 2024,
  • [25] Boosting Symbolic Execution for Heap-based Vulnerability Detection and Exploit Generation
    Tu, Haoxin
    2023 IEEE/ACM 45TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: COMPANION PROCEEDINGS, ICSE-COMPANION, 2023, : 218 - 220
  • [26] Towards Auto Contract Generation and Ensemble-based Smart Contract Vulnerability Detection
    Puducherry, K. Lakshminarayana
    Puducherry, K. Sathiyamurthy
    INTERNATIONAL JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING SYSTEMS, 2022, 13 (09) : 747 - 757
  • [27] RTMS: A Smart Contract Vulnerability Detection Method Based on Feature Fusion and Vulnerability Correlations
    Gao, Gaimei
    Li, Zilu
    Jin, Lizhong
    Liu, Chunxia
    Li, Junji
    Meng, Xiangqi
    ELECTRONICS, 2025, 14 (04):
  • [28] An integrated deep learning model for Ethereum smart contract vulnerability detection
    Jain, Vikas Kumar
    Tripathi, Meenakshi
    INTERNATIONAL JOURNAL OF INFORMATION SECURITY, 2024, 23 (01) : 557 - 575
  • [29] Vulnerability Detection for Smart Contract via Backward Bayesian Active Learning
    Zhang, Jiale
    Tu, Liangqiong
    Cai, Jie
    Su, Xiaobing
    Li, Bin
    Chen, Weitong
    Wang, Yu
    APPLIED CRYPTOGRAPHY AND NETWORK SECURITY WORKSHOPS, ACNS 2022, 2022, 13285 : 66 - 83
  • [30] Smart Contract Vulnerability Detection: The Role of Large Language Model (LLM)
    Boi, Biagio
    Esposito, Christian
    Lee, Sokjoon
    APPLIED COMPUTING REVIEW, 2024, 24 (02): : 19 - 29