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COUNT TEN (Conspiracy to Launder Money)
56. Paragraphs 1 through 19, 21 through 49, and 55 are re-alleged and incorporated by reference as if fully set forth herein.
57. To facilitate the purchase of infrastructure used in their hacking activity—including hacking into the computers of U.S. persons and entities involved in the 2016 U.S. presidential election and releasing the stolen documents—the Defendants conspired to launder the equivalent of more than $95,000 through a web of transactions structured to capitalize on the perceived anonymity of cryptocurrencies such as bitcoin.
58. Although the Conspirators caused transactions to be conducted in a variety of currencies, including U.S. dollars, they principally used bitcoin when purchasing servers, registering domains, and otherwise making payments in furtherance of hacking activity. Many of these payments were processed by companies located in the United States that provided payment processing services to hosting companies, domain registrars, and other vendors both international and domestic. The use of bitcoin allowed the Conspirators to avoid direct relationships with traditional financial institutions, allowing them to evade greater scrutiny of their identities and sources of funds.
59. All bitcoin transactions are added to a public ledger called the Blockchain, but the Blockchain identifies the parties to each transaction only by alpha-numeric identifiers known as bitcoin addresses. To further avoid creating a centralized paper trail of all of their purchases, the Conspirators purchased infrastructure using hundreds of different email accounts, in some cases using a new account for each purchase. The Conspirators used fictitious names and addresses in order to obscure their identities and their links to Russia and the Russian government. For example, the dcleaks.com domain was registered and paid for using the fictitious name “Carrie Feehan” and an address in New York. In some cases, as part of the payment process, the Conspirators provided vendors with nonsensical addresses such as “usa Denver AZ,” “gfhgh ghfhgfh fdgfdg WA,” and “1 2 dwd District of Columbia.”