Smurfing is a type of structuring tactic where financial transactions are broken into smaller amounts to evade detection. Often associated with traditional banking and now increasingly prevalent in crypto, smurfing allows criminals to avoid reporting thresholds, bypass monitoring systems, and obscure the trail of illicit funds.
This article explores how smurfing works across both fiat and digital asset environments, when and why cybercriminals deploy it, and how it can be used not just for threshold evasion but as a layering technique in money laundering. It also outlines how blockchain analytics can help detect and disrupt smurfing in practice.
Smurfing is the practice of structuring transactions to evade detection by financial institutions, regulators, or internal monitoring systems. It’s commonly used in traditional financial crime—such as when individuals split large cash payments into smaller increments under $10,000 to avoid triggering IRS Form 8300 reporting requirements. For example, a car buyer might pay $9,500 in cash one day and return the next day to pay the remaining balance, deliberately avoiding the threshold that would require the dealership to report the transaction.
This tactic is also prevalent in the cryptocurrency sector. In the European Union, under the Transfer of Funds Regulation (TFR), Crypto-Asset Service Providers (CASPs) are required to conduct customer due diligence (CDD) for transactions amounting to €1,000 or more. To evade these checks, a criminal might divide a larger sum into multiple transfers, each just below the €1,000 threshold, and route them through various wallets or accounts. This method allows illicit transactions to proceed without triggering the mandated CDD procedures.
Smurfing is designed to exploit binary regulatory thresholds and rule-based detection systems, slipping beneath the radar of compliance teams and automated tools that tend to flag only large or anomalous transactions. By consistently operating just below these lines, criminals can make illicit financial activity appear routine, significantly complicating detection and enforcement.
Smurfing can be used in various ways throughout the laundering process, serving different purposes depending on the context and controls being evaded.
To avoid triggering reporting thresholds - Many financial regulations require institutions to report transactions that exceed specific thresholds. For example, under the U.S. Bank Secrecy Act (BSA), banks must report any cash transactions over $10,000 in a single day. To evade detection, individuals may use a tactic known as “smurfing”—structuring transactions just below the threshold across multiple days, such as sending $2,000 daily over five days.
Similar strategies may also be used to circumvent crypto-specific regulations. The Financial Action Task Force (FATF), an intergovernmental body, introduced the Travel Rule in 1996 and expanded it in 2019 to cover Virtual Asset Service Providers (VASPs). The rule mandates the sharing of originator and beneficiary information for cryptocurrency transactions exceeding certain thresholds—$3,000 in the United States and $1,000 in many other jurisdictions.
To avoid alerting monitoring - Smurfing isn’t always used to avoid regulatory thresholds—it can also be employed to bypass internal monitoring systems. For example, a single large withdrawal from a VASP’s hot wallet might trigger an immediate response from the security team, prompting them to investigate, isolate the breach, and suspend key functions like withdrawals. In contrast, a series of smaller withdrawals may appear as routine activity, giving attackers more time to siphon and launder funds undetected.
This tactic was used in the NoOnes hack in January 2025. Although the total loss amounted to $7.9 million, the attackers executed hundreds of transactions across Ethereum, Tron, Solana, and BNB—each kept below $7,000. This smurfing strategy may have delayed NoOnes' response. Initially, the company cited routine maintenance, and it wasn’t until several weeks later—following an exposé by third-party investigator ZachXBT—that the CEO publicly confirmed the breach.
The incident illustrates how smurfing can effectively obscure malicious activity, delay detection, and hinder timely incident response.
To add to layering - Smurfing, while often associated with avoiding regulatory thresholds, is also frequently used as a layering technique in money laundering. The goal isn’t always to stay under a specific limit—it can also be to fragment the transaction trail, making it harder for investigators to trace the movement of illicit funds.
Smurfing, at its core, involves breaking up large sums of money into smaller transactions across multiple transfers, wallets, or accounts. Within this broader tactic, there are more specific techniques—one example is the peel chain. A peel chain is a structured laundering method in which funds are transferred through a sequence of wallets, with smaller amounts being “peeled off” at each step. It differs from arbitrary smurfing in that the amounts progressively decrease across each hop, creating a predictable, yet complex, laundering pattern.
This method was notably used by the DMM hacker in May 2024. Instead of sending random amounts, the hacker followed a clear peel chain pattern—starting with a large transfer of 499 BTC in the first hop, then gradually decreasing the amount to 39 BTC by the third hop. This structured fragmentation made it significantly harder to trace the stolen funds and identify exit points.
Policies that rely on rigid, binary thresholds—such as those defined by the Travel Rule—are inherently vulnerable to exploitation. When rules are public and absolute, criminals can easily adapt, deliberately structuring transactions just below the stated limits. This tactic isn’t limited toAanti-Money Laundering (AML) rules like the Travel Rule or Know-Your-Customer (KYC) requirements; it also applies to tax reporting thresholds, daily transfer caps, and platform-specific withdrawal limits.
Smurfing also tends to outsmart traditional cybersecurity defenses. Security teams are typically trained to detect anomalies—such as sudden spikes in transaction volume or unusually large withdrawals—that signal potential breaches. But when illicit activity mimics legitimate business behavior, such as a steady stream of smaller, routine transactions, it becomes nearly indistinguishable to the human eye and often goes undetected.
This is where blockchain analytics becomes a critical tool. Unlike threshold-based policies, behavior-based rule engines can flag suspicious patterns, even when each individual transaction appears harmless. For example, a CASP in Europe might use blockchain analytics software to detect a user who regularly sends transactions just under €1,000—potentially a deliberate effort to evade customer due diligence. With customizable rules, the system could flag the pattern and prompt additional verification or review.
Beyond prevention, these systems also support incident response. In the event of a breach, even if the attacker uses smurfing to fragment the trail, blockchain analytics tools can reconstruct the flow of funds through transaction graphing—tracing the laundering path across wallets, protocols, and even cross-chain bridges. While no solution is 100% foolproof, behavior-based analytics significantly increase the chances of early detection and successful investigation.
Smurfing is a powerful tactic used by criminals to evade detection and exploit regulatory gaps in both fiat and crypto systems. As explored in this article, it’s not just about staying under thresholds—it’s also a method for bypassing monitoring and adding complexity to laundering trails. Merkle Science offers tools to combat these risks: Compass, a behavior-based rule engine that flags suspicious transaction patterns, and Tracker, an investigative platform that traces complex fund flows. Together, these solutions equip compliance teams to detect smurfing activity in real time and take swift, data-driven action to protect their platforms.
