The Fall of Garantex: A Tactical Win, But Money Laundering Persists

The recent arrest of Aleksej Besciokov, a key administrator of crypto exchange Garantex, one of the most prolific money laundering platforms in the crypto ecosystem, marks a significant step in disrupting a major laundering operation but falls short of a decisive blow.

Despite OFAC sanctions in place from 2022, Garantex continued processing billions of dollars in illicit funds, particularly through Tron and Ethereum blockchains. The recent seizure of Garantex's domain prevents users from accessing its front-end website—but the core infrastructure, including wallets, databases, and trading engines, likely remains operational, especially if hosted in jurisdictions resistant to international cooperation.

Users displaced by the seizure won't simply vanish; they will pivot quickly. Past crackdowns offer vivid evidence of this:

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Where Will Garantex Users Migrate Next?

Below is a list of potential destinations where Garantex users may migrate to continue their illicit activities:

• Mirror Exchanges: Illicit platforms often rebrand under new domains while retaining the same infrastructure, operations, and user base. For example, Blender rebranded as Sinbad after sanctions, continuing its mixing services under a new identity while preserving its laundering methods.
• New Infrastructure, Same Brand: If servers are compromised, operators may migrate data to new hosting providers and relaunch under the same name. Users can still be directed to the new platform through previously known wallet addresses, OTC desk connections, or private communication channels.
• Decentralized and P2P Channels: Telegram groups, decentralized swaps, and OTC desks absorbing displaced illicit volumes. For example, after Hydra was sanctioned and shut down, researchers observed increased chatter on Telegram about new “cash out” services and mixers to replace its functionality
• State-Supported Alternatives:  Migration to Russian-based exchanges with weak compliance (e.g. P2P platforms). 

Garantex’s fall represents a tactical enforcement accomplishment—but the broader fight against crypto laundering requires evolving compliance methods to match the speed and ingenuity of illicit actors to achieve victory.

Garantex’s Money Laundering Playbook: Techniques That Still Exist

Garantex’s sophisticated crypto laundering strategies have set a persistent standard that continues to inspire and influence similar illicit operations throughout the crypto space. Understanding these tactics is crucial for compliance teams to detect and intercept future threats. We’ve outlined below some of the most common laundering tactics used by Garantex:

• High-Frequency Hot Wallet Rotation: Garantex routinely rotated its hot wallets (approximately every five hours), complicating tracing efforts significantly. The rapid turnover disrupted address clustering analysis, allowing funds to move without being flagged by conventional risk-scoring models. With Merkle Science’s advanced heuristics and real-time monitoring, new hot wallets and deposit addresses can be identified within one minute of their first activity, enabling compliance teams to swiftly counteract this tactic.

• Layered Wallet Handovers: Funds were deliberately transferred through multiple intermediary wallets in intricate, multi-layered transaction paths, intentionally fragmenting transaction histories to hinder traceability and compliance detection. With Merkle Science’s AI-driven suspicious behavior detection, compliance teams can automatically uncover advanced laundering patterns—layering, peel chains, micro transfers, rapid fund dispersion, and wallet clustering anomalies—in seconds, enabling them to trace, risk-score, and block illicit flows before they reach exit points.

• Fixed Gas Fee Deposits: Depositors consistently prefunded fixed amounts designated specifically for gas fees, a methodical laundering hallmark. This regular and predictable behavior cleverly evaded automated transaction monitoring systems. With Merkle Science’s customizable rule engine, compliance officers can set specific detection thresholds for recurring fixed-fee deposits, a common laundering tactic. AI-driven behavioral analytics then automatically flag and correlate these anomalies with broader laundering patterns, enabling proactive risk mitigation.

• Preference for Tron: Garantex notably favored Tron and other EVM chains due to their lower transaction fees, higher speed, and lighter scrutiny compared to Bitcoin. While Garantex largely abandoned Bitcoin operations by late 2022 due to increased oversight, EVM chains and Tron continued to facilitate illicit transactions until November 2024.
  • Tron (TRX): Capable of 2,000 TPS with 3-second blocks, offering low fees, abundant liquidity, and rapid transaction speed—ideal for illicit actors needing fast, low-risk laundering.
  • EVM Chains: Leveraged DEXs, cross-chain bridges, and privacy-focused swaps to complicate tracking and obfuscate fund movement.

With Merkle Science’s industry-leading coverage of sanctioned actors on Tron and our extensive High Risk Entities (HRE) dataset—comprising millions of addresses, including 250+ unique entities not covered elsewhere— compliance teams can detect, trace, and risk-score illicit crypto transactions with precision, enabling proactive enforcement against evolving laundering tactics.

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Garantex’s On-Chain Data: Unpacking the Scale of Operations

To gain a deeper understanding of Garantex’s operational scale and illicit transaction patterns, our research team conducted a comprehensive analysis of nearly 1 million blockchain addresses linked to Garantex across Tron (TRX), Bitcoin (BTC), Ethereum (ETH), and Binance Smart Chain (BSC). 

This targeted on-chain analytics approach allowed us to quantify the financial scope of illicit flows, identify vulnerabilities exploited by illicit actors, and provide actionable insights for compliance teams.

Here are some key insights from our deep dive into Garantex operations:

• Dominance of Tron: Tron was the dominant chain for Garantex, processing 89.76% of total inflows. Tron transactions were nearly 9x higher than those on Ethereum and Binance Smart Chain (BSC).
• Ethereum & BSC: Ethereum and BSC collectively accounted for approximately 10.1% of analyzed inflows, illustrating deliberate diversification to spread risk and complicate detection.
• Sanctioned Entity Exposure: An overwhelming majority of OFAC-sanctioned inflows were processed across Tron, Ethereum, and Binance Smart Chain, with Tron as the dominant network, reinforcing its role in illicit fund movement.

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                                                                     Figure 1: Illicit Fund Movements to Garantex

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Garantex’s Persistent Compliance Gaps and Strategic Adaptations:

Despite sanctions, Garantex-linked addresses continued moving significant volumes of illicit funds, demonstrating the resilience and adaptability of its laundering infrastructure. Over $530 million flowed into just two major regulated exchanges—not due to weak compliance alone, but because Garantex systematically manipulated transaction patterns to bypass detection mechanisms.

Zooming out, the broader exposure is even more concerning: approximately $4 billion flowed into well-known centralized exchanges (CEXs), with nearly an equivalent amount ($3.8 billion) flowing outward. This 1:1 ratio of inflows to outflows strongly suggests Garantex did not operate as a conventional exchange but rather as a high-volume pass-through entity, —a transient stop used specifically to obscure fund origins and destinations.

These vulnerabilities were not just compliance failures at CEXs but a result of Garantex’s deliberate adaptations to evade detection. It refined its tactics by rotating hot wallets frequently, shifting blockchains, and transactions through intermediary wallets, fragmenting audit trails to bypass risk scoring.

Beyond standard laundering activity, Garantex also facilitated financial crime linked to designated terrorist organizations, with over $16 million traced to Hezbollah-linked addresses alone. The platform’s ability to continue processing these transactions post-sanctions underscores critical weaknesses in cross-border enforcement and sanctions screening, especially when illicit actors operate within jurisdictions that provide regulatory shelter.

To combat these evolving threats, compliance teams must move beyond static rule-based detection and adopt AI-driven behavioral analytics that automatically detect suspicious laundering patterns in real-time. The ability to correlate high-frequency transactions across multiple blockchains, identify coordinated fund movements, and flag rapid address turnover is critical to staying ahead of sophisticated laundering operations like Garantex.

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Evolving Crypto Compliance: Moving Beyond Static Monitoring

Garantex’s takedown highlights a critical shift—rule-based detection is no longer enough. Illicit actors don’t disappear after enforcement—they migrate, adapt, and evolve. The next Garantex will emerge in new forms, on new chains, using new obfuscation tactics. 

To effectively combat these adaptive threats, compliance teams must move beyond static screening based on known entity names  and focus on implementing real-time behavior detection and proactive measures, including:

• Leveraging Dark Web & Telegram Intelligence – Monitor vendor migration trends across darknet forums, escrow services, and P2P groups. Tracking OTC advertisements, cash-out services, and laundering networks in real-time can provide early warnings of emerging threats.
• Deploying Real-Time Risk Scoring Based on Transaction Behavior – Rather than flagging transactions based on set thresholds, use dynamic risk scoring models that adapt based on transaction patterns ––– wallets repeatedly sending fixed amounts, using privacy-enhancing tools, or displaying erratic behavior should be automatically escalated for deeper review.
• Identifying Garantex-Linked Deposit & Withdrawal Patterns – Garantex relied on recurring gas fee deposits and structured withdrawals to obscure transaction origins. Compliance teams should implement detection rules tailored to these patterns, identifying repetitive, uniform deposit behaviors that mirror past laundering tactics.
• Analyzing Velocity & Frequency  – Sudden wallet activity spikes, high-frequency fund transfers, and structured small-value deposits often indicate obfuscation attempts. Setting dynamic thresholds for unusual velocity shifts can help identify laundering early on.
• Tracking High-Risk P2P & OTC Patterns – Launderers increasingly use unregulated OTC brokers, Telegram escrow services, and P2P platforms to cash out illicit funds. Flagging high-frequency trades, structured payments, and recurring counterparties in high-risk regions can help detect illicit networks before they reach exchanges.

To stay ahead, compliance programs must learn and adapt as fast as illicit actors do. The future of crypto transaction monitoring isn’t about chasing flagged wallets—it’s about detecting the next Garantex before it exists. Book a Merkle Science demo today to strengthen your crypto compliance strategy.

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