Galaxy Digital's testnet suffers hack but no client funds or information were compromised

Tech Share Share this article Copy link X icon X (Twitter) LinkedIn Facebook Email Galaxy Digital's testnet suffers hack but no client funds or information were compromised Mike Novogratz’s crypto financial services firm said unauthorized access was limited to a segregated R&D workspace; trading systems and client accounts were unaffected. By Will Canny , AI Boost | Edited by Aoyon Ashraf Apr 1, 2026, 5:48 p.m. Make preferred on Galaxy Digital CEO Mike Novogratz. (CoinDesk) What to know : Unauthorized access was limited to an isolated R&D workspace, not production systems. Galaxy says no client funds or account data were accessed or at risk. All trading platforms and services remain fully functional and unaffected, the firm said. Galaxy Digital (GLXY), the digital asset financial services firm founded by Mike Novogratz, said it recently contained a cybersecurity incident involving unauthorized access to an isolated development workspace, according to a statement from a company spokesperson. "An immaterial amount of company funds used for testing within the isolated development workspace was impacted," the spokesperson said in emailed comments. The loss was less than $10,000, according to a person with knowledge of the matter. The firm emphasized that the affected environment was used solely for research and development and was not connected to its core infrastructure, production systems, trading platforms or client accounts. Galaxy said it detected the intrusion and moved quickly to contain it, secure the compromised workspace and implement additional precautionary measures across its on-chain infrastructure. “No client funds or client account information were accessed or at risk at any point based on our review to date,” Galaxy said, adding that all platforms and services remain fully operational and secure for clients. Hacks and exploits remain a persistent risk in the crypto industry, where the combination of open-source code, large pools of onchain liquidity and uneven security practices creates an attractive target for attackers. Billions of dollars are lost to smart contract exploits, phishing schemes and infrastructure breaches, with industry estimates often exceeding $1–2 billion annually in recent years. Even when incidents are contained, and client assets are not impacted, breaches can erode trust, trigger heightened regulatory scrutiny and underscore the operational risks facing firms operating in largely irreversible, always-on financial systems. Galaxy is a diversified financial services and investment firm focused on the digital asset and blockchain sector, providing institutional clients with trading, asset management, lending, advisory and custody services. The firm operates across several core business lines, including global markets, asset management and digital infrastructure, while also running businesses in areas like crypto mining, staking and data center operations. Positioned as a bridge between traditional finance and crypto, Galaxy offers institutional-grade access to digital assets and related technologies, alongside investments in blockchain ventures and emerging areas such as AI-powered infrastructure. The company said it is continuing to review the incident and will provide updates as appropriate. Read more: Bitcoin’s quantum threat is real, but far from an existential crisis, Galaxy says Hack Exclusive Galaxy Digital AI Disclaimer: Parts of this article were generated with the assistance from AI tools and reviewed by our editorial team to ensure accuracy and adherence to our standards . For more information, see CoinDesk's full AI Policy . More For You Encryption Supremacy: Zcash and Privacy in the Age of Scale By CoinDesk Research Mar 31, 2026 Commissioned by GenZcash Most crypto privacy models weaken as blockchain data grows. Encryption-based models like Zcash strengthen. CoinDesk Research maps the five privacy approaches and examines the widening gap. Why it matters : As blockchain adoption scales, the metadata available to machine learning models scales with it. Obfuscation-based privacy approaches are structurally degrading as a result. 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