heimdall-rs

Heimdall is an advanced EVM smart contract toolkit specializing in bytecode analysis and extracting information from unverified contracts. Heimdall is written in Rust and is designed to be fast, modular, and more accurate than other existing tools. Use it to navigate the topic and choose relevant methods, papers or tools.

Editorial note: curated source snapshot published by Collider.club under the MIT License. Source attribution is preserved in the front matter.

Source snapshot

heimdall-rs

Overview

Heimdall is an advanced EVM smart contract toolkit specializing in bytecode analysis and extracting information from unverified contracts. Heimdall is written in Rust and is designed to be fast, modular, and more accurate than other existing tools.

Currently, Heimdall supports the following operations:

• EVM Bytecode Disassembly
• EVM Smart-Contract Control Flow Graph Generation
• EVM Smart-Contract Decompilation
• Smart-Contract Storage Dumping
• Raw Transaction Calldata Decoding
• Raw Transaction Trace Decoding

Installation & Usage

Ensure that Rust & Cargo are installed:

curl https://sh.rustup.rs -sSf | sh

Heimdall's update and installation manager, bifrost, can be installed using the following command:

curl -L http://get.heimdall.rs | bash

If you want to manually install bifrost, you can download the latest release from here.

Once you have installed bifrost, you can use it to install Heimdall using the following command from a new terminal:

bifrost

After compilation, the heimdall command will be available to use from a new terminal. For advanced options, see the bifrost documentation.

Having trouble? Check out the Troubleshooting section in the wiki.

Documentation

Documentation for all of heimdall-rs is available in the wiki.

Contributing

If you'd like to contribute to Heimdall or add a module, please open a pull-request with your changes, as well as detailed information on what is changed, added, or improved.

For more detailed information, see the contributing guide.

Issues

If you've found an issue or have a question, please open an issue here. All issues must follow their respective templates.

Credits

Heimdall is a research-based toolkit created and maintained by Jonathan Becker. A full list of our 20+ contributors can be found in the sidebar.

If interested in the research behind Heimdall, check out some of my publications.

Academic Citations

Heimdall has been cited in the following academic papers & theses:

• Aimar, D. (2023). Extraction, indexing, and analysis of Ethereum smart contracts data [Master’s thesis, Politecnico di Torino]. Webthesis. http://webthesis.biblio.polito.it/id/eprint/28450
• Chen, Z., Beillahi, S. M., Barahimi, P., Minwalla, C., Du, H., Veneris, A., & Long, F. (2025). Secure smart contract with control flow integrity. arXiv. https://doi.org/10.48550/arXiv.2504.05509
• Darwish, M. (2024). From bytecode to safety: Decompiling smart contracts for vulnerability analysis [Bachelor’s thesis, Linnaeus University]. DiVA Portal. https://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-129903
• De Rosa, P., Felber, P., & Schiavoni, V. (2026). Seeing through EVM bytecode obfuscation. IEEE Access, 14, 25515–25536. https://ieeexplore.ieee.org/document/11373339
• Forissier, T. (2024). EVeilM: EVM bytecode obfuscation [Master’s thesis, KTH Royal Institute of Technology]. DiVA Portal. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-359674
• Gkioka, M. (2025). Domain transfer via decompilation: Enhancing code LLMs’ performance for blockchain applications [Master’s thesis, National and Kapodistrian University of Athens]. Pergamos. https://pergamos.lib.uoa.gr/uoa/dl/object/5296079
• Lagouvardos, S., Bollanos, Y., Debono, M., Grech, N. & Smaragdakis, Y. (2025). Precise static identification of Ethereum storage variables. arXiv. https://doi.org/10.48550/arXiv.2503.20690
• Lagouvardos, S., Bollanos, Y., Grech, N., & Smaragdakis, Y. (2025). The incredible shrinking context…in a decompiler near you. arXiv. https://doi.org/10.48550/arXiv.2409.11157
• Liao, Z., Nan, Y., Gao, Z., Liang, H., Hao, S., Ren, P., & Zheng, Z. (2025). Augmenting smart contract decompiler output through fine-grained dependency analysis and LLM-facilitated semantic recovery. arXiv. https://doi.org/10.48550/arXiv.2501.08670
• Liu, Y., Li, X., & Li, Y. (2025). DeepTx: Real-time transaction risk analysis via multi-modal features and LLM reasoning. arXiv. https://doi.org/10.48550/arXiv.2510.18438
• Peng, C., Jiang, M., Zhou, Y., & Wu, L. (2026). Thought is all you need: Smart contract vulnerability detection with thought-augmented large language model. Proceedings of the ACM on Software Engineering, 3(FSE). https://doi.org/10.1145/3808141
• Qasse, I. A. (2025). Immutable yet mutable: Empirical studies in smart contract upgradeability [Doctoral dissertation, Reykjavík University]. Iris. https://iris.ru.is/ws/files/235971434/Thesis_Smart_contract_upgradeability_Final_.pdf
• Qasse, I., Hamdaqa, M., & Jónsson, B. Þ. (2025). PROXiFY: A bytecode analysis tool for detecting and classifying proxy contracts in Ethereum smart contracts. In ASE 2025: Proceedings of the 40th IEEE/ACM International Conference on Automated Software Engineering (pp. 4114–4117). IEEE. https://doi.org/10.1109/ASE63991.2025.00388
• Qin, K., Song, D., & Gervais, A. (2026). SCDBench: A benchmark for LLM-based smart contract decompilers. arXiv. https://doi.org/10.48550/arXiv.2605.29059
• Solmaz, O., Heimbach, L., Vonlanthen, Y., & Wattenhofer, R. (2025). Optimistic MEV in Ethereum layer 2s: Why blockspace is always in demand. arXiv. https://doi.org/10.48550/arXiv.2506.14768
• Su, X., Wu, H., Liang, H., Jiang, Y., Cheng, Y., Liu, Y., & Xu, F. (2026). From transactions to exploits: Automated PoC synthesis for real-world DeFi attacks. arXiv. https://doi.org/10.48550/arXiv.2601.16681
• Sun, Y., Bao, L., & Yang, X. (2025). FIRE: Smart contract bytecode function identification via graph-refined hybrid feature encoding. ACM. https://doi.org/10.1145/3755881.3755883
• Wang, Z., Yu, J., Qin, K., Song, D., Gervais, A., & Zhou, L. (2026). TxRay: Agentic postmortem of live blockchain attacks. arXiv. https://doi.org/10.48550/arXiv.2602.01317
• Ye, M., Lin, X., Nan, Y., Wu, J., & Zheng, Z. (2024). Midas: Mining profitable exploits in on-chain smart contracts via feedback-driven fuzzing and differential analysis. In M. Christakis & M. Pradel (Eds.), ISSTA 2024: Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis (pp. 794–805). Association for Computing Machinery. https://doi.org/10.1145/3650212.3680321

If you have used or plan to use Heimdall in your research, please reach out to me via email or Twitter! I'd love to hear about what you're using heimdall for :)

About Collider.club

This card belongs to the curated knowledge base of Collider.club — a closed business club for entrepreneurs, engineers, investors and domain experts building projects for international markets. Members work across DeFi, AI/ML, FinTech, Web3, banking, hardware and venture capital, and the club runs closed sessions on high-margin niches with anonymous speakers.

• Club: https://collider.club
• Collection: Collider.club curated card library (mdrss-card/v2)
• Maintainer: Collider.club editorial team

License

MIT License — Copyright (c) 2026 Collider.club. Full text: LICENSE · https://opensource.org/licenses/MIT