Comparison of Static and Dynamic Analysis for Solidity Smart Contract Vulnerability Detection

Authors

  • Andreas Perdana Universitas Dharmawacana Metro, Metro, Indonesia Author
  • Febri Sugandi Universitas Dharmawacana Metro, Metro, Indonesia Author
  • Ridwan Yusuf✉ Universitas Dharmawacana Metro, Metro, Indonesia Author
  • Untoro Apsiswanto Universitas Dharmawacana Metro, Metro, Indonesia Author
Diajukan 20 Sep 2025 Diterbitkan 20 Des 2025
DOI: https://doi.org/10.59025/a948780c

Keywords:

smart contract, static analysis, dynamic analysis, vulnerability detection, ethereum

Abstract

Smart contracts on the Ethereum platform manage financial assets of significant value, yet their immutable nature renders any code vulnerability permanently exploitable as demonstrated by The DAO, Parity Wallet, and Ronin Bridge incidents. Two vulnerability detection approaches have developed in parallel: static analysis that inspects source code or bytecode without execution, and dynamic analysis that runs contracts in simulated environments with structured inputs. Each carries different trade-offs in speed, coverage, and false-positive rate, yet systematic comparisons within Indonesian local development settings using the latest tool versions remain scarce. This article presents the design of a quantitative experimental study that will compare Slither (static) against Foundry and Echidna (dynamic) on a dataset of 25 Solidity smart contracts covering five major vulnerability categories: reentrancy, integer overflow, access control, unchecked return values, and unbounded loop. Comparison metrics include precision, recall, F1-score, and computation time. The expected contribution is a comparative framework that can serve as a practical reference for Indonesian Web3 developers in choosing security tools and hybrid testing strategies appropriate to project risk level and team resources.

References

  1. Z. Liu et al., "Combining Graph Neural Networks With Expert Knowledge for Smart Contract Vulnerability Detection," IEEE Transactions on Knowledge and Data Engineering, 2023, doi: 10.1109/TKDE.2021.3095196.
  2. S. S. Kushwaha et al., "Systematic Review of Security Vulnerabilities in Ethereum Blockchain Smart Contract," IEEE Access, 2022, doi: 10.1109/ACCESS.2021.3140091.
  3. P. Tolmach et al., "A Survey of Smart Contract Formal Specification and Verification," ACM Computing Surveys, 2023, doi: 10.1145/3464421.
  4. B. Boi dan C. Esposito, "Prompt Engineering vs. Fine-Tuning for LLM-Based Vulnerability Detection in Solana and Algorand Smart Contracts," dalam Proc. 2025 7th International Conference on Blockchain Computing and Applications (BCCA), 2025, doi: 10.1109/bcca66705.2025.11229457.
  5. C. Kado dan T. Tsuchiya, "Initial Attempt at Automated Vulnerability Fixing of Obfuscated Smart Contracts Using a Large Language Model," dalam Proc. 2024 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia), 2024, doi: 10.1109/icce-asia63397.2024.10773661.
  6. S. Mane, J. Bhortake, V. Wankhade, dan F. Kazi, "Automated IoT Firmware Vulnerability Detection Using Large Language Models," Preprints, 2025, doi: 10.20944/preprints202510.0166.v1.
  7. H. Taherdoost, "Smart Contracts in Blockchain Technology: A Critical Review," Information, vol. 14, no. 2, hal. 117, 2023, doi: 10.3390/info14020117.
  8. S. Y. Lin, L. Zhang, J. Li, L. L. Guo, dan Y. Lin, "A survey of application research based on blockchain smart contract," Wireless Networks, 2022, doi: 10.1007/s11276-021-02874-x.
  9. L. Ante, "The Non-Fungible Token (NFT) Market and Its Relationship with Bitcoin and Ethereum," FinTech, 2022, doi: 10.3390/fintech1030017.
  10. N. Karandikar, A. Chakravorty, dan C. Rong, "Blockchain based transaction system with fungible and non-fungible tokens for a community-based energy infrastructure," Sensors, vol. 21, no. 11, hal. 3822, 2021, doi: 10.3390/s21113822.
  11. J. Wu et al., "Who Are the Phishers? Phishing Scam Detection on Ethereum via Network Embedding," IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, doi: 10.1109/TSMC.2020.3016821.
  12. J. Arcenegui, R. Arjona, R. Roman, dan I. Baturone, "Secure combination of IoT and blockchain by physically binding IoT devices to smart non-fungible tokens using PUFs," Sensors, vol. 21, no. 9, hal. 3119, 2021, doi: 10.3390/s21093119.
  13. E. Moayyed, C. Anumba, dan A. Morteza, "Systematic analysis of large language models for automating document-to-smart contract transformation," Automation in Construction, 2025, doi: 10.1016/j.autcon.2025.106209.
  14. D. Kirli et al., "Smart contracts in energy systems: A systematic review of fundamental approaches and implementations," Renewable and Sustainable Energy Reviews, 2022, doi: 10.1016/j.rser.2021.112013.
  15. H. Hamledari dan M. Fischer, "Construction payment automation using blockchain-enabled smart contracts and robotic reality capture technologies," Automation in Construction, 2021, doi: 10.1016/j.autcon.2021.103926.
  16. A. P. Balcerzak, E. Nica, E. Rogalska, M. Poliak, T. Klieštik, dan O.-M. Sabie, "Blockchain Technology and Smart Contracts in Decentralized Governance Systems," Administrative Sciences, vol. 12, no. 3, hal. 96, 2022, doi: 10.3390/admsci12030096.
  17. G. D. Ritterbusch dan M. R. Teichmann, "Defining the Metaverse: A Systematic Literature Review," IEEE Access, 2023, doi: 10.1109/ACCESS.2023.3241809.
  18. K. B. Wilson, A. Karg, dan H. Ghaderi, "Prospecting non-fungible tokens in the digital economy: Stakeholders and ecosystem, risk and opportunity," Business Horizons, 2022, doi: 10.1016/j.bushor.2021.10.007.
  19. B. Hammi, S. Zeadally, R. Adja, M. El Madhoun, dan J. Nebhen, "Non-Fungible Tokens: A Review," IEEE Internet of Things Magazine, 2023, doi: 10.1109/IOTM.001.2200244.
  20. M. Turki, S. Cheikhrouhou, B. Dammak, M. Baklouti, R. Mars, dan A. Dhahbi, "NFT-IoT Pharma Chain: IoT Drug traceability system based on Blockchain and Non Fungible Tokens (NFTs)," Journal of King Saud University - Computer and Information Sciences, 2023, doi: 10.1016/j.jksuci.2022.12.016.
  21. L. Ante, "Non-fungible token (NFT) markets on the Ethereum blockchain: temporal development, cointegration and interrelations," Economics of Innovation and New Technology, 2023, doi: 10.1080/10438599.2022.2119564.
  22. L. Cao, "Decentralized AI: Edge Intelligence and Smart Blockchain, Metaverse, Web3, and DeSci," IEEE Intelligent Systems, 2022, doi: 10.1109/MIS.2022.3181504.
  23. H. Albayati, S. K. Kim, dan J. J. Rho, "Accepting financial transactions using blockchain technology and cryptocurrency: A customer perspective approach," Technology in Society, 2020, doi: 10.1016/j.techsoc.2020.101320.
  24. L. Ma, Z. Yang, Z. Bu, Q. Lao, dan W. Yang, "Statement Recognition of Access Control Policies in IoT Networks," Sensors, vol. 23, no. 18, hal. 7935, 2023, doi: 10.3390/s23187935.
  25. I. Ghosh, S. Alfaro-Cortes, M. Galindo, dan J. M. Sanchez-Garcia, "Prediction and interpretation of daily NFT and DeFi prices dynamics: Inspection through ensemble machine learning & XAI," International Review of Financial Analysis, 2023, doi: 10.1016/j.irfa.2023.102558.
  26. S. Casale-Brunet, P. Ribeca, P. Doyle, dan M. Mattavelli, "Networks of Ethereum Non-Fungible Tokens: A graph-based analysis of the ERC-721 ecosystem," dalam Proc. 2021 IEEE International Conference on Blockchain (Blockchain), 2021, doi: 10.1109/Blockchain53845.2021.00033.
  27. J. Köpke, G. Meroni, dan M. Salnitri, "Towards Automated Handling of Object State Exceptions in Smart Contracts," dalam Lecture Notes in Business Information Processing, 2025, doi: 10.1007/978-3-032-02936-2_13.
  28. Y. Liu, S. Chan, J. Chu, Y. Zhang, dan Y. Chen, "When LLM Meets Simplicial Complex: A Novel Graph Prompt Learning on Ethereum Transaction Networks," dalam Proc. 2025 IEEE International Conference on Data Mining (ICDM), 2025, doi: 10.1109/icdm65498.2025.00148.
  29. J. Truby, R. D. Brown, A. Dahdal, dan I. Ibrahim, "Blockchain, climate damage, and death: Policy interventions to reduce the carbon emissions, mortality, and net-zero implications of non-fungible tokens and Bitcoin," Energy Research & Social Science, 2022, doi: 10.1016/j.erss.2022.102499.
  30. L. Wu, K. Lu, F. Xue, dan W. Lu, "A blockchain non-fungible token-enabled 'passport' for construction waste material cross-jurisdictional trading," Automation in Construction, 2023, doi: 10.1016/j.autcon.2023.104783.
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How to Cite

Comparison of Static and Dynamic Analysis for Solidity Smart Contract Vulnerability Detection. (2025). Journal of Technology and Data Science, 3(2), 204-215. https://doi.org/10.59025/a948780c