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title: Home
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---
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{:.lead .text-center}
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GraphSense is a cryptoasset analytics platform emphasizing full data sovereignty, algorithmic transparency, and scalability. GraphSense is open-source and free. It provides a dashboard for interactive investigations and, more importantly, complete data control for automatizing cryptoasset analytics workflows.
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<divclass="container mt-3">
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<pclass="lead text-center">
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GraphSense is a cryptoasset analytics platform emphasizing full data sovereignty, algorithmic transparency, and scalability. GraphSense is open-source and free. It provides a dashboard for interactive investigations and, more importantly, complete data control for automatizing cryptoasset analytics workflows.
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</p>
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</div>
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## Origin & Background
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GraphSense originated in 2015 as a publicly funded research project at the [Austrian Institute of Technology (AIT)](https://www.ait.ac.at){:target="_blank"}, led by [Bernhard Haslhofer](https://bernhardhaslhofer.info/){:target="_blank"} as Principal Investigator. Since then, development has been carried out in collaboration with the [Complexity Science Hub](https://www.csh.ac.at){:target="_blank"} and has been supported by several public funding programs, including the Austrian FFG ([IKT der Zukunft](https://iktderzukunft.at/en/projects/graph-sense.php){:target="_blank"}, [KIRAS](https://www.kiras.at/){:target="_blank"}), and the EU Horizon 2020 program ([TITANIUM](https://www.titanium-project.eu/){:target="_blank"}).
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In 2021, the core development team founded [Iknaio Cryptoasset Analytics GmbH](https://www.iknaio.com){:target="_blank"} to provide GraphSense as a hosted service with near real-time data updates and to develop additional operational tools — such as [Pathfinder](https://www.iknaio.com/platform){:target="_blank"}, [CaseConnect](https://www.iknaio.com/platform#caseconnect){:target="_blank"}, and [QuickLock](https://www.iknaio.com/platform#quicklock){:target="_blank"} — on top of the open-source platform.
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<p>GraphSense originated in 2015 as a publicly funded research project at the <ahref="https://www.ait.ac.at"target="_blank">Austrian Institute of Technology (AIT)</a>, led by <ahref="https://bernhardhaslhofer.info/"target="_blank">Bernhard Haslhofer</a> as Principal Investigator. Since then, development has been carried out in collaboration with the <ahref="https://www.csh.ac.at"target="_blank">Complexity Science Hub</a> and has been supported by several public funding programs, including the Austrian FFG (<ahref="https://iktderzukunft.at/en/projects/graph-sense.php"target="_blank">IKT der Zukunft</a>, <ahref="https://www.kiras.at/"target="_blank">KIRAS</a>), and the EU Horizon 2020 program (<ahref="https://www.titanium-project.eu/"target="_blank">TITANIUM</a>).</p>
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GraphSense itself remains fully open-source and [MIT-licensed](https://github.com/graphsense){:target="_blank"}. Iknaio is the commercial service and development partner; the two are complementary, not competing.
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<p>In 2021, the core development team founded <ahref="https://www.iknaio.com"target="_blank">Iknaio Cryptoasset Analytics GmbH</a> to provide GraphSense as a hosted service with near real-time data updates and to develop additional operational tools — such as <ahref="https://www.iknaio.com/platform"target="_blank">Pathfinder</a>, <ahref="https://www.iknaio.com/platform#caseconnect"target="_blank">CaseConnect</a>, and <ahref="https://www.iknaio.com/platform#quicklock"target="_blank">QuickLock</a> — on top of the open-source platform.</p>
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## Supported Assets
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<p>GraphSense itself remains fully open-source and <ahref="https://github.com/graphsense"target="_blank">MIT-licensed</a>. Iknaio is the commercial service and development partner; the two are complementary, not competing.</p>
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</div>
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{:.lead .text-center .mb-5}
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The GraphSense system design supports UTXO- (e.g., Bitcoin) and account-model (e.g., Ethereum, Tron) ledgers. Currently, adapters are available for major cryptocurrencies like Bitcoin, Bitcoin Cash, Litecoin, Zcash, Ethereum and Tron. Additional ledgers can be integrated by implementing a lightweight adapter component.
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## Supported Assets
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<divclass="container">
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<pclass="lead mb-5 text-center">The GraphSense system design supports UTXO- (e.g., Bitcoin) and account-model (e.g., Ethereum, Tron) ledgers. Currently, adapters are available for major cryptocurrencies like Bitcoin, Bitcoin Cash, Litecoin, Zcash, Ethereum and Tron. Additional ledgers can be integrated by implementing a lightweight adapter component.</p>
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<divclass="row"style="justify-content:center">
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{% for currency in site.data.currencies %}
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{% assign curr = currency[0] %}
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{% assign stats=currency[1] %}
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{% include currency.html stats=stats currency=curr %}
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{% endfor %}
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</div>
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</div>
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## Features
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<ulclass="container features d-flex flex-row flex-wrap w-100">
Haslhofer, B., Stütz, R., Romiti, M., & King, R. (2021). **GraphSense: A general-purpose cryptoasset analytics platform.** arXiv preprint. [(pdf)](https://arxiv.org/abs/2102.13613)
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<p>Haslhofer, B., Stütz, R., Romiti, M., & King, R. (2021). GraphSense: A general-purpose cryptoasset analytics platform. Arxiv pre-print.
title = {GraphSense: A General-Purpose Cryptoasset Analytics Platform},
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author = {Bernhard Haslhofer and Rainer Stütz and Matteo Romiti and Ross King},
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year = {2021},
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journal = {Arxiv pre-print},
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url = {https://arxiv.org/abs/2102.13613}
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}
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</code></pre></div></div>
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</div>
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```bibtex
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@article{Haslhofer:2021a,
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title = {GraphSense: A General-Purpose Cryptoasset Analytics Platform},
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author = {Bernhard Haslhofer and Rainer Stütz and Matteo Romiti and Ross King},
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year = {2021},
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journal = {arXiv preprint},
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url = {https://arxiv.org/abs/2102.13613}
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}
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```
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## Scientific Studies
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GraphSense has already supported several scientific studies:
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<divclass="container">
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Stütz, R., Stifter, N., Dragaschnig, M., Haslhofer, B., & Judmayer, A. (2026). **Reuse of Public Keys Across UTXO and Account-Based Cryptocurrencies.** arXiv preprint. [(pdf)](https://arxiv.org/abs/2601.19500)
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<p>GraphSense has already supported several scientific studies:</p>
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Avice, R., Haslhofer, B., Li, Z., & Zhou, J. (2026). **Linking cryptoasset attribution tags to knowledge graph entities: An LLM-based approach.** Financial Cryptography and Data Security (FC 2026). [(pdf)](https://fc25.ifca.ai/preproceedings/74.pdf)
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<p>Stütz, R., Stifter, N., Dragaschnig, M., Haslhofer, B., & Judmayer, A. (2026). <strong>Reuse of Public Keys Across UTXO and Account-Based Cryptocurrencies.</strong> arXiv preprint.
Saggese, P., Segalla, E., Sigmund, M., Raunig, B., Zangerl, F., & Haslhofer, B. (2024). **Assessing the solvency of virtual asset service providers: Are current standards sufficient?** Applied Economics. [(pdf)](https://www.tandfonline.com/doi/abs/10.1080/00036846.2024.2396640)
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<p>Avice, R., Haslhofer, B., Li, Z., & Zhou, J. (2026). <strong>Linking cryptoasset attribution tags to knowledge graph entities: An LLM-based approach.</strong> Financial Cryptography and Data Security (FC 2026).
Niedermayer, T., Saggese, P., & Haslhofer, B. (2024). **Detecting financial bots on the Ethereum blockchain.** Companion Proceedings of the ACM Web Conference 2024. [(pdf)](https://doi.org/10.1145/3589335.3651959)
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<p>Saggese, P., Segalla, E., Sigmund, M., Raunig, B., Zangerl, F., & Haslhofer, B. (2024). <strong>Assessing the solvency of virtual asset service providers: Are current standards sufficient?</strong> Applied Economics.
Haslhofer, B., Hanslbauer, C., Fröwis, M., & Goger, T. (2023). **Increasing the efficiency of cryptoasset investigations by connecting the cases.** APWG Symposium on Electronic Crime Research (eCrime 2023). [(pdf)](https://docs.apwg.org/ecrimeresearch/2023/20240328851329400.pdf)
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<p>Niedermayer, T., Saggese, P., & Haslhofer, B. (2024). <strong>Detecting financial bots on the Ethereum blockchain.</strong> Companion Proceedings of the ACM Web Conference 2024.
Stütz, R., Stockinger, J., Haslhofer, B., Moreno-Sanchez, P., & Maffei, M. (2022). **Adoption and actual privacy of decentralized CoinJoin implementations in bitcoin.** Proceedings of the 4th ACM Conference on Advances in Financial Technologies (AFT 2022). [(pdf)](https://arxiv.org/abs/2109.10229)
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<p>Haslhofer, B., Hanslbauer, C., Fröwis, M., & Goger, T. (2023). <strong>Increasing the efficiency of cryptoasset investigations by connecting the cases.</strong> APWG Symposium on Electronic Crime Research (eCrime 2023).
Kappos, G., Yousaf, H., Stütz, R., Rollet, S., Haslhofer, B., & Meiklejohn, S. (2022). **How to peel a million: Validating and expanding bitcoin clusters.** 31st USENIX Security Symposium (USENIX Security 22). [(pdf)](https://www.usenix.org/conference/usenixsecurity22/presentation/kappos)
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<p>Stütz, R., Stockinger, J., Haslhofer, B., Moreno-Sanchez, P., & Maffei, M. (2022). <strong>Adoption and actual privacy of decentralized CoinJoin implementations in bitcoin.</strong> Proceedings of the 4th ACM Conference on Advances in Financial Technologies (AFT 2022).
Romiti, M., Victor, F., Moreno-Sanchez, P., Nordholt, P., Haslhofer, B., & Maffei, M. (2021). **Cross-layer deanonymization methods in the lightning protocol.** Financial Cryptography and Data Security (FC 2021). [(pdf)](https://arxiv.org/abs/2007.00764)
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<p>Kappos, G., Yousaf, H., Stütz, R., Rollet, S., Haslhofer, B., & Meiklejohn, S. (2022). <strong>How to peel a million: Validating and expanding bitcoin clusters.</strong> 31st USENIX security symposium (USENIX security 22).
Stütz, R., Gaži, P., Haslhofer, B., & Illum, J. (2020). **Stake shift in major cryptocurrencies: An empirical study.** Financial Cryptography and Data Security (FC 2020). [(pdf)](https://arxiv.org/abs/2001.04187)
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<p>Romiti, M., Victor, F., Moreno-Sanchez, P., Nordholt, P., Haslhofer, B., & Maffei, M. (2021). <strong>Cross-layer deanonymization methods in the lightning protocol.</strong> Financial cryptography and data security (FC 2021).
Paquet-Clouston, M., Romiti, M., Haslhofer, B., & Charvat, T. (2019). **Spams meet Cryptocurrencies: Sextortion in the Bitcoin Ecosystem.** Advances in Financial Technologies (AFT 2019). [(pdf)](https://arxiv.org/abs/1908.01051)
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<p>Stütz, R., Gaži, P., Haslhofer, B., & Illum, J. (2020). <strong>Stake shift in major cryptocurrencies: An empirical study.</strong> Financial cryptography and data security (FC 2020).
Romiti, M., Judmayer, A., Zamyatin, A., & Haslhofer, B. (2019). **A Deep Dive into Bitcoin Mining Pools: An Empirical Analysis of Mining Shares.** Workshop on the Economics of Information Security (WEIS 2019). [(pdf)](https://arxiv.org/abs/1905.05999)
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<p>Paquet-Clouston, M., Romiti, M., Haslhofer, B., & Charvat, T. (2019). <strong>Spams meet Cryptocurrencies: Sextortion in the Bitcoin Ecosystem.</strong> Advances in Financial Technologies (AFT 2019).
Paquet-Clouston, M., Haslhofer, B., & Dupont, B. (2019). **Ransomware payments in the bitcoin ecosystem.** Journal of Cybersecurity, 5(1). [(pdf)](https://arxiv.org/abs/1804.04080)
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<p>Romiti, M., Judmayer, A., Zamyatin, A., & Haslhofer, B. (2019). <strong>A Deep Dive into Bitcoin Mining Pools: An Empirical Analysis of Mining Shares.</strong> Workshop on the Economics of Information Security (WEIS 2019).
Filtz, E., Polleres, A., Karl, R., & Haslhofer, B. (2017). **Evolution of the Bitcoin Address Graph - An Exploratory Longitudinal Study.** International Data Science Conference (DSC 2017). [(pdf)](https://aic.ai.wu.ac.at/~polleres/publications/filtz-etal-2017IDSC.pdf)
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<p>Paquet-Clouston, M., Haslhofer, B., & Dupont, B. (2019). <strong>Ransomware payments in the bitcoin ecosystem.</strong> Journal of Cybersecurity, 5(1).
<p>Filtz, E., Polleres, A., Karl, R., & Haslhofer, B. (2017). <strong>Evolution of the Bitcoin Address Graph - An Exploratory Longitudinal Study.</strong> International Data Science Conference (DSC 2017).
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