Summary
- Chainalysis Reactor’s evidentiary admissibility has now withstood scrutiny at two levels of federal court. In September, the D.C. Circuit upheld a previous U.S. District Court ruling that the Chainalysis platform “easily clears the threshold for reliability” under the Daubert standard.
- The decision reinforces the foundation on which Reactor is built. The appellate court pointed to multiple factors supporting the platform’s reliability, including its clustering methodology as well as its track record and widespread use by law enforcement and private-sector specialists.
- A tested methodology matters more than ever as blockchain analytics and AI scale. More powerful tools require a reliable foundation. The appellate decision provides further independent validation of the principles behind our work, giving us greater confidence as we build the next generation of investigation tools.
Chainalysis Reactor passed its first major legal test in 2024 when a U.S. court found it met the threshold for admissibility as evidence at trial. We wrote about that decision earlier this year.
Now an appellate court has upheld this original decision.
In the original case, United States v. Sterlingov, dual Swedish-Russian national Roman Sterlingov was found guilty of operating the crypto mixer service “Bitcoin Fog.” Reactor was used to examine the transactions between Bitcoin Fog and a variety of darknet markets, ultimately attributing to Bitcoin Fog over 900,000 Bitcoin addresses. The evidence was supported by expert testimony from FBI Specialist Luke Scholl and Chainalysis expert Elizabeth Bisbee, who testified about Reactor’s methodologies, validation, and application in the investigation.
During the trial, Sterlingov sought to block Reactor evidence and related expert testimony, arguing it was inadmissible. The court turned away his claims, finding instead that Reactor met the Daubert standard, a framework courts use to assess the reliability of expert testimony.
Sterlingov sought to overturn his guilty verdict in an appeal where he once again challenged the admissibility of Reactor, arguing that it should not meet the Daubert standard. Ruling on the appeal, the D.C. Circuit upheld the District Court’s decision to admit Reactor-based testimony.
This is significant beyond the Sterlingov case itself. The appellate court’s decision validates that Reactor’s underlying methodology can withstand scrutiny, and withstand it time over time.
Ultimately, the court’s assessment rested not on any single Daubert factor, but on a broader body of evidence around Reactor’s methodology and performance. Its conclusion was that Reactor is based on reliable principles and methods — providing further confidence in the continued use of Reactor for investigations, compliance, and other high-stakes applications.
To date, Chainalysis is the only blockchain analytics platform to have been tested against the Daubert standard.
How Chainalysis withstood a second round of scrutiny
When appealing his conviction, Sterlingov argued that Reactor-derived evidence and related expert testimony should not have been admitted. The U.S. Court of Appeals for the D.C. Circuit rejected that challenge in September, finding no error in the District Court’s decision to admit evidence from Reactor.
The appellate court cited a range of evidence supporting the product’s reliability. This included the platform’s clustering attribution methodology, which combines change address analysis with digital fingerprinting to identify addresses exhibiting matching transaction patterns and behavioral characteristics, as well as its widespread use among law enforcement and private-sector specialists. The court also cited testimony from Scholl and Bisbee, both of whom said they could not recall a time in which a Reactor attribution had later proven incorrect.
One of the aspects of Sterlingov’s appeal that the court considered was his argument that Reactor was unreliable because it had not been peer-reviewed and had no known error rate. The appellate court was not persuaded, noting that peer review is not necessarily expected for technology operating in a relatively new and specialized field such as blockchain analysis. It’s worth noting, however, that independent academic researchers published a granular evaluation of blockchain analysis in 2025 and confirmed Chainalysis data is the most accurate and reliable with the lowest false positive rate and highest coverage.
The court further highlighted Reactor’s deliberately conservative approach to attribution, treating it as a positive. The court recognized that an underinclusive methodology can support reliability by prioritizing defensible connections over making connections simply because they are possible.
Why methodological rigor matters as blockchain analytics and AI scale
The consequences of getting an attribution wrong can be significant. An incorrect connection can send an investigation in the wrong direction or lead to poor risk or compliance decisions. The impact can also extend beyond a single investigation, undermining confidence in the broader analytical process.
As blockchain analytics becomes more powerful and widely adopted, the stakes only increase. More organizations are relying on attribution data for high-stakes decisions, often at scale and with little room for error, putting greater pressure on the methodology behind each attribution.
AI raises the stakes even further. This is because AI can accelerate a sound methodology, not fix a weak one. When the foundation is flawed, greater scale only magnifies the problem. There is so much opportunity for AI to help in investigations, as was the case in our team’s recent work on the $387 million Bitget hack. But the underlying data needs to be reliable.
That is what makes this new appellate decision significant — Reactor’s methodology has now been found reliable at two levels of federal court. For us, it is more than a legal milestone. It is independent validation of the foundation we are building as we develop the next generation of blockchain investigation tools.
FAQs
What is the Daubert standard in U.S. federal courts?
The Daubert standard is a legal test U.S. federal courts use to determine whether expert scientific or technical testimony is reliable enough to be admitted as evidence at trial. Judges may consider factors such as whether a method can be tested, whether it has undergone peer review, its potential error rate, and whether it is generally accepted in the relevant field. The standard helps courts assess the reliability of expert evidence before it is presented to a jury.
Did Chainalysis Reactor pass the Daubert standard on appeal?
Yes. In September 2026, the U.S. Court of Appeals for the D.C. Circuit upheld the District Court’s decision to admit evidence derived from Chainalysis Reactor in United States v. Sterlingov. The ruling upheld the admission of Reactor-based evidence and related expert testimony, meaning the platform’s evidentiary admissibility withstood scrutiny at both the district court and appellate levels.
When did Chainalysis originally pass the Daubert standard?
Chainalysis was subjected to the Daubert standard in the 2024 case United States v. Sterlingov when a federal court considered a challenge to expert testimony based on Chainalysis Reactor. The court ruled in favor of its reliability.
Is Chainalysis the only blockchain analytics provider to successfully meet the Daubert standard?
Yes. Chainalysis is the first and only blockchain analytics provider to successfully meet the Daubert standard as of October 2026.
Why did the courts find Chainalysis Reactor reliable under the Daubert standard?
The courts considered several factors supporting Reactor’s reliability, including its clustering methodology, track record, and widespread use by law enforcement and private-sector specialists. The appellate court also cited expert testimony supporting its reliability and recognized Reactor’s conservative approach to attribution, which prioritizes defensible connections between cryptocurrency addresses over speculative links.
Why does this decision matter going forward?
Reactor’s admissibility at both the district court and appellate levels provides further independent validation of the methodology underpinning Chainalysis’ approach to blockchain investigations. This foundation matters as Chainalysis develops the next generation of investigation tools. AI and other technological advances can accelerate analysis, but they cannot compensate for unreliable data or flawed methodology.
This website contains links to third-party sites that are not under the control of Chainalysis, Inc. or its affiliates (collectively “Chainalysis”). Access to such information does not imply association with, endorsement of, approval of, or recommendation by Chainalysis of the site or its operators, and Chainalysis is not responsible for the products, services, or other content hosted therein.
This material is for informational purposes only, and is not intended to provide legal, tax, financial, or investment advice. Recipients should consult their own advisors before making these types of decisions. Chainalysis has no responsibility or liability for any decision made or any other acts or omissions in connection with Recipient’s use of this material.
Chainalysis does not guarantee or warrant the accuracy, completeness, timeliness, suitability or validity of the information in this report and will not be responsible for any claim attributable to errors, omissions, or other inaccuracies of any part of such material.
