Blockchain analytics traces transactions, clusters addresses and labels entities to determine which wallets are connected and what risk they carry; Plastron applies these techniques to your wallet free across seven EVM chains.
Blockchain Analytics Explained
Blockchain analytics traces cryptocurrency transactions across the entire public ledger to identify which addresses are connected, what entities control them, and what risk they represent.
Blockchain analytics is the discipline of analyzing public blockchain data to extract intelligence about transaction patterns, address ownership, and fund flows. Unlike traditional financial analytics, which relies on private bank records, blockchain analytics works entirely from publicly accessible data: every transaction on Ethereum and Bitcoin is permanently recorded and readable by anyone. The challenge is not accessing the data — it is making sense of it at scale. The core techniques in blockchain analytics are transaction tracing, address clustering, and entity labelling. Transaction tracing follows the flow of funds through a chain of transactions: given an address of interest, trace which addresses sent it funds, which addresses those received from, and how far back the chain extends. This allows analysts to identify whether funds in a wallet ultimately originated from a known bad actor, even if they passed through multiple intermediate addresses. Address clustering groups multiple wallet addresses that are likely controlled by the same entity, based on behavioral patterns in their transactions — common input ownership in Bitcoin, or consistent gas payment patterns in Ethereum. Entity labelling maps specific wallet addresses or clusters to known organizations: exchanges, DeFi protocols, bridges, mixers, and flagged entities. These labels come from a combination of public information (exchange deposit addresses are published in blockchain explorers), voluntary disclosure (companies sharing their addresses for compliance purposes), and intelligence gathering (addresses identified from darknet monitoring, law enforcement data sharing, and user reports). The output of blockchain analytics — a risk score, a list of flagged counterparties, a fund flow diagram — is what exchange compliance systems use to decide whether to accept or investigate a deposit. Understanding how this works helps you understand why your wallet might be flagged even if you believe your activity is entirely legitimate.
How Plastron Helps
Counterparty Graph Visualization
Plastron's Sankey diagram shows the top sources and destinations of funds in your wallet, classified by entity type. This fund flow visualization is the most accessible form of blockchain analytics output — it shows you where your money came from and where it went, in the same format that exchange compliance systems use internally to review incoming deposits.
Entity Classification and Risk Attribution
The analytical value of blockchain analytics comes from entity classification — knowing that a given address belongs to Binance, or Tornado Cash, or Lazarus Group. Plastron classifies counterparties across fourteen entity types and flags those that carry AML risk. This entity context is what converts a list of anonymous addresses into a readable compliance report.
Activity Pattern Detection
Beyond counterparty analysis, Plastron's activity heatmap applies statistical analysis to your transaction timing and frequency. Anomalies — clusters of transactions that deviate significantly from your baseline pattern — are flagged and visualized. This behavioral analytics layer is what compliance systems use to identify structuring, rapid-cycling, and other transactional patterns that may indicate money laundering independent of the counterparties involved.
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