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Criminals are increasingly hopping across blockchains to cover their tracks — and it’s working. Elliptic has traced more than $21 billion in illicit crypto activity routed through cross-chain services as of May 2025, roughly triple its 2023 estimate, forcing investigators to rebuild how they follow the money.
The growth of cross-chain tracking reflects a broader change in crypto investigations. Rather than following funds from one wallet to another on the same network, investigators increasingly have to establish relationships between transactions that occur on different blockchains and may involve different technical structures.
Research cited by Analytics Insight shows the scale of the challenge. Elliptic identified more than $21 billion in cumulative illicit and high-risk activity routed through cross-chain services by May 2025, approximately three times its 2023 estimate. The figure represents identified activity accumulated through that period rather than losses occurring exclusively during 2025.
Chainalysis, meanwhile, estimated that illegal addresses received at least $154 billion in 2025, with stablecoins accounting for 84% of illicit transaction volume.
These figures underscore why cross-chain tracking increasingly extends beyond Bitcoin-focused investigations.
Traditional blockchain analysis can be relatively straightforward when funds remain on one network. Investigators can examine wallet addresses, transaction histories and timestamps through that blockchain’s records.
The picture becomes more complicated when assets move between networks.
A bridge can lock or otherwise process assets on one blockchain while corresponding value is released or issued on another. From an investigative perspective, the challenge is establishing that the transactions on both networks represent the same movement of value.
That is where cross-chain tracking becomes relevant.
Some blockchain systems provide transaction identifiers or other information that can help investigators directly match activity. In other cases, analysts may have to compare several characteristics, including transaction amounts, timing, addresses and the behavior of the services involved.
The process can become more difficult when transactions include fees, asset conversions or aggregation. A single transaction on one network may not have an obvious one-to-one equivalent on another, requiring investigators to consider several pieces of evidence before establishing a connection.
Elliptic’s research found that 33% of investigations involved more than three blockchains, while 20% extended across more than 10 networks. The findings demonstrate the increasingly fragmented environment investigators must navigate when examining suspicious cryptocurrency activity.
The technical challenge has also created demand for new research into automated methods of identifying relationships between transactions.
An August 2026 study classified transfer-matching techniques into three broad categories: deterministic identifiers, field constraints and model-assisted methods. The research emphasized that the reliability of each approach depends heavily on the evidence available from the systems being investigated, including information that exists outside the blockchain itself.
This distinction is important because cross-chain tracking is not simply a matter of searching for identical transaction records across networks.
Different blockchains operate according to different technical architectures. Their transaction data can be structured differently, and the way assets are represented or transferred can vary substantially.
A method that works effectively on one network may therefore require significant adaptation before being applied elsewhere.
That challenge is particularly evident in research involving Solana.
A September 10, 2026 preprint introduced SolTracer, a proposed method for matching transfers into Solana despite differences in the network’s execution structure. Researchers reported a 20.16% improvement in F1 score compared with their strongest comparison method under the specified experimental conditions.
The finding represents a research result rather than a universal measure of accuracy or evidence that the system has been adopted by law-enforcement agencies.
Still, it illustrates the direction of cross-chain tracking research: investigators and researchers need systems that account for the individual characteristics of different blockchains rather than applying identical assumptions across every network.
While better analytics can make crypto investigations more efficient, tracing transactions does not automatically establish who controls a wallet or whether a particular person participated in criminal activity.
A transaction trail can show how assets moved. It cannot, by itself, establish identity, motive or criminal intent.
That distinction becomes particularly important when funds pass through exchanges, bridges, swap services or other intermediaries. Investigators may identify an address or service associated with a transaction, but additional evidence may be necessary to determine the significance of that connection.
The source material also highlights concerns around reproducibility. A review found that fewer than half of the assessed datasets and research artifacts remained obtainable. For blockchain investigation research, this means that the ability to reproduce findings can be as important as achieving strong performance figures in an individual experiment.
Consequently, cross-chain tracking works most effectively as part of a broader investigative process involving transaction analysis, external records, corroborating evidence and appropriate legal procedures.
Asset recovery presents another challenge. Finding the route taken by cryptocurrency does not necessarily mean investigators can recover it. Recovery can depend on whether assets remain accessible, whether they reach a service that can be compelled to cooperate and whether authorities can legally intervene.
The expansion of interconnected blockchain ecosystems is changing the way cryptocurrency investigations are conducted.
Criminal actors can move assets between networks to complicate transaction analysis, while legitimate users increasingly rely on bridges, exchanges and other services to move value across blockchain ecosystems. The same infrastructure that expands the utility of digital assets can therefore make financial investigations more complex.
Cross-chain tracking provides a way to preserve continuity across those fragmented records by attempting to connect transactions that occur on separate networks.
Its usefulness, however, depends on the quality of the underlying evidence. Investigators must distinguish confirmed transaction relationships from analytical assumptions and avoid treating exposure to a suspicious address or service as proof of criminal conduct.
The development of tools such as SolTracer suggests that researchers are continuing to address gaps created by differences between blockchain architectures. At the same time, the limited availability of some research datasets highlights the need for transparent and reproducible methodologies.
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