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The D.C. Circuit upheld admission of Chainalysis Reactor evidence in United States v. Sterlingov, extending a prior district court Daubert ruling.
Chainalysis said its Reactor blockchain analytics platform has now survived Daubert scrutiny in two levels of federal court after the U.S. Court of Appeals for the D.C. Circuit upheld a district court ruling admitting Reactor-based testimony in United States v. Sterlingov. The decision matters because it extends a case-specific evidentiary ruling that Chainalysis says strengthens the legal foundation for its attribution methodology in investigations and compliance work.
Evidence and context
In the underlying Sterlingov case, a federal court found in 2024 that Reactor met the threshold for admissibility as evidence at trial, according to Chainalysis and the materials provided. The D.C. Circuit later affirmed the conviction on Sept. 25, 2026, and the company’s Oct. 13, 2026 post says the appellate court rejected Sterlingov’s renewed challenge to Reactor’s admissibility. The company said the appellate court relied on multiple factors, including Reactor’s clustering methodology, its track record and its use by law enforcement and private-sector specialists.
According to Chainalysis, the Sterlingov case involved evidence linking Bitcoin Fog to darknet-market activity, with Reactor used to examine transaction flows and attribute more than 900,000 Bitcoin addresses to the mixer service. The company also said expert testimony from FBI Specialist Luke Scholl and Chainalysis expert Elizabeth Bisbee supported the methodology at trial. The appellate court, Chainalysis said, was not persuaded by arguments that Reactor was unreliable because it had not been peer reviewed or assigned a known error rate, noting that peer review is not necessarily expected in a relatively new and specialized field such as blockchain analysis.
The company’s explanation of Reactor describes a conservative approach to attribution, using clustering rules that combine change address analysis with digital fingerprinting to identify addresses showing matching transaction patterns and behavioral characteristics. Background material supplied with the request says Chainalysis distinguishes between direct attribution and clustering, and that its methodology favors underinclusion, which can leave some related addresses outside a cluster. That background also notes the D.C. Circuit’s decision is a case-specific evidentiary ruling, not a universal certification of every Reactor output or an overall error rate.
Chainalysis framed the ruling as independent validation of its methodology as blockchain analytics and AI tools become more widely used. The company also pointed to academic research published in 2025 that it says found Chainalysis data to have the lowest false positive rate and highest coverage among the systems studied. No market data were provided for Reactor or any related token, and the source material does not supply a next verified catalyst date beyond the appellate ruling already noted.
