The "Coin Farm" Case Study: How Carding Laundered Millions of Dollars Using In-Game Items and Cryptocurrency

[Professor]

Analysis of a Specific, Complex, Multi-Step Scheme​

Preface: This case study is based on real-life investigations, woven together into a complex hybrid scheme typical of the mid-2020s. It demonstrates the evolution of laundering: from direct cashing to the use of virtual economies and decentralized finance (DeFi).

Context and Participants​

• Organizers: A technical team of 3-4 people (Russia/CIS). They were involved in classic carding (purchasing CVV databases, phishing, and soshing).
• Problem: Classic cash-out methods (droppers, mules) had become too popular. A highly liquid, anonymous, and less traceable channel for money laundering was needed.
• Solution: Use the game economy (primarily CS:GO, Dota 2, and World of Warcraft) as a "digital laundromat" and then transfer capital into cryptocurrency.

Diagram: Five-stage conveyor​

STEP 1: LOOT THE "DIRTY" FIAT

• Action: Standard carding. Stolen card data was used to purchase digital game codes (Steam codes, Battle.net top-up codes, Xbox Gift Cards) on specialized aggregator websites.
• Why codes and not products? Speed and no logistics. A 20-character code can be obtained and transmitted in seconds. There are no droppers, parcels, or cameras at the pickup point.
• Volumes: Operations amounted to ~5-7 million rubles per month.

STEP 2: LOADING INTO THE "VIRTUAL ECONOMY"

• Action: Codes purchased with stolen money were used to top up accounts on Steam and Battle.net platforms.
• The following were purchased using these balances:
  1. Expensive in-game items (skins) with high and stable demand: Knives and gloves in CS:GO; Arcana and ultra-rare items in Dota 2.
  2. Game currency (gold) in MMORPG (World of Warcraft) through official services (WoW Token) or purchase from farmers.
• The goal: to convert "hot" fiat money tied to cards into virtual, yet liquid, assets whose origins are extremely difficult to trace. Steam and its games are becoming a giant criminal exchange point.

STEP 3: "REMELTING" AND CUTTING OFF THE TRACE

• Action 1 (for skins): A network of controlled Steam trader accounts was created. Expensive skins purchased on "dirty" accounts were transferred between dozens of accounts through the platform's trading system. Trading bots were used to simulate normal activity. As a result, the items ended up on "clean" accounts unrelated to the original purchases.
• Action 2 (for game currency): In WoT, fictitious "sales" of items or characters were carried out between controlled accounts for gold in order to move and concentrate it.
• The essence of this stage: To confuse the chain of ownership within gaming ecosystems that do not promptly cooperate with the police on such requests.

STEP 4: WITHDRAWAL INTO "SEMI-PURE" FIAT OR CRYPTO
This is the key and most risky stage. There were two main channels:

1. P2P sales on external platforms:
   • "Clean" accounts with expensive skins were put up for sale on out-of-game marketplaces (for example, DMarket, SkinBaron, or Russian-language forums).
   • The buyers were ordinary gamers who wanted to buy a skin cheaper than the official Steam commission.
   • Payment was accepted only in cryptocurrency (USDT). Thus, the virtual asset was converted into a cryptoasset, divorced from the original crime.
2. Using unregulated exchangers:
   • Game currency (gold) or accounts were sold through specialized websites and Telegram channels for crypto or even "pure" fiat (transferred to the cards of front men), but with a huge commission (30-40%).

STEP 5: THE FINAL LAUNCH IN DeFi

• Action: Cryptocurrency (mostly USDT) obtained from the sale of game assets was run through decentralized finance (DeFi) protocols.
• Method: Crypto mixers on the Ethereum blockchain (e.g. Tornado Cash before sanctions) and cross-blockchain swaps (from Tron to Ethereum via bridges) were used.
• The goal: To completely sever the blockchain connection between the recipient wallet from the skin sale and the organizers' wallet. After this, the "cleaned" funds could be withdrawn to legitimate crypto exchanges with liberal KYC requirements or cashed out via OTC transactions.

Weaknesses of the scheme and points of failure​

Despite its sophistication, the scheme had vulnerabilities:

1. Steam activity patterns: Mass purchases of expensive items from new accounts followed by quick trades could be detected by Valve's (Steam) platform security algorithms, which banned accounts for "fraudulent transactions." This resulted in the loss of invested funds.
2. Blockchain: While DeFi mixers made surveillance difficult, crypto forensics (such as from Chainalysis) could, with some degree of certainty, link incoming and outgoing transactions, especially if an error was made during the P2P sale (such as accessing a regulated exchange from a single wallet).
3. The human factor at the intersection: Selling accounts or skins for fiat via instant messengers led to contact with "clients" who could prove problematic (police, competitors, or simply troublemakers filing complaints).
4. Law enforcement intervention: With proper coordination between the police cyber department (Department "K") and financial monitoring, it was possible to trace the chain: suspicious card transactions → purchasing codes from specific aggregators → identifying the Steam accounts on which these codes were activated.

Results and implications of the case​

1. Scale: Over 9 months of operation, the scheme allowed for the laundering of approximately $1,000,000
2. Distribution of damages:
   • Banks/cardholders: Direct losses from carding.
   • Gaming platforms (Valve, Blizzard): Indirect damage to reputation, burden on support services, distortion of the in-game economy.
   • End-users of skins: Often unaware that they were funding a criminal scheme by purchasing items.
3. The fate of the participants: Organizers often face charges in similar cases. Sellers on P2P platforms who actively worked with them could be charged as accomplices. Game accounts and items were seized as evidence.

Conclusion: The "Coin Farm" case is a clear example of the convergence of cybercrime, virtual economies, and decentralized finance. It demonstrated that modern carding is more than just theft and withdrawal. It is complex financial engineering, where gaming worlds become buffer zones for money laundering, and decentralized technologies become the final shield of anonymity. Combating such schemes requires unprecedented cooperation between financial intelligence, cyberpolice, blockchain experts, and… gaming platform administrators, who are often reluctant to delve into such investigations, seeing them as a threat only to external payment systems, not to their own ecosystem.