U.S. Court Admits Chainalysis Reactor Analysis Under Daubert in Bitcoin Fog Case

Daubert Review in the Sterlingov Case

In the case, prosecutors alleged that Roman Sterlingov operated Bitcoin Fog, which they said was used to launder tens of millions of dollars tied to illicit darknet activity. The defense moved to exclude Chainalysis expert testimony, prompting the court to examine whether Reactor’s clustering and attribution methods were sufficiently reliable for trial.

Under the Daubert standard, drawn from a 1993 U.S. Supreme Court decision, judges act as gatekeepers for expert evidence. Courts assess whether a methodology can be tested, whether it has been reviewed by other experts, whether its error rate is known or controlled, and whether it is broadly accepted in the relevant field. A method does not need to satisfy every factor perfectly, but the framework is used to measure whether the reasoning behind the evidence is reliable.

How the Court Assessed Reactor

Judge Randolph Moss evaluated Reactor against those factors and concluded that the methodology was admissible in this case. On testability, the court found Reactor’s clustering and attribution process transparent enough that its conclusions could be independently verified.

On peer review and publication, the court said Reactor relies on commonly accepted heuristics for analyzing and grouping spending activity. The source article notes that Reactor itself had not been peer reviewed at the time of the hearing, although a peer-reviewed study in 2025 later attested to its precision. The court also pointed to the co-spend heuristic as one that has long been discussed in academic literature.

For error rate, the article says FBI analyst Luke Scholl testified that he had not encountered false positives in his experience. The court also highlighted Reactor’s conservative design, describing it as tending toward underinclusion rather than overclaiming addresses, a feature the judge said helps reduce the risk of false positives.

On general acceptance, the court found that Chainalysis data is widely used by law enforcement, regulators, exchanges, financial institutions, and compliance teams. According to the article, the court also credited evidence that Chainalysis is viewed as an industry-standard tool and is used across multiple U.S. government agencies and major exchanges.

Defense Objections and Broader Limits

A central defense argument was that Reactor functioned as a “black-box” algorithm whose outputs could not be meaningfully examined. The ruling rejected that characterization, finding instead that the methodology was transparent, testable, auditable, and reliable enough for substantive evidence.

The article also stresses that the government’s case did not rely on Chainalysis alone. Prosecutors used additional evidence and techniques, including traditional forensic traces, IP logs, confession, and forum posts, alongside blockchain analysis.

At the same time, the ruling was presented as narrow. It did not amount to a blanket endorsement of blockchain analytics as a category, and it did not validate every analytics provider’s methods. The decision addressed only whether Chainalysis Reactor’s methodology satisfied Daubert in this particular case.

Chainalysis framed the outcome as an example of public-blockchain tracing methods surviving close evidentiary scrutiny when they are transparent and corroborated. The company also pointed to its recently published ontology for blockchain attribution, which it said sets out how clusters are built and what standards each component must meet. In the Bitcoin Fog case, however, the court’s task was limited to the evidence before it and the reliability of Reactor’s methods as presented in United States v. Sterlingov.