Transaction Monitoring¶

What Is DeFi Transaction Monitoring?¶

DeFi transaction monitoring means verifying wallet addresses before they interact with your protocol - preventing fraudulent, sanctioned, or high-risk addresses from connecting, depositing, or executing transactions.

In traditional finance, AI fraud models rely on rich identity data: account histories, device databases, credit card records. In DeFi, the blockchain address is the only data point. ChainAware's AI is purpose-built for this constraint - scoring risk entirely from on-chain behaviour patterns across 20M+ wallet profiles.

How It Works for DeFi Protocols¶

DeFi protocols subscribe via https://swagger.chainaware.ai
Validate wallet addresses when they connect to your dApp using the real-time API
If an address is flagged as high fraud risk, block it from connecting or transacting via Web3 API
Results are returned in under 100ms - no user-perceptible latency

Predictive Power¶

The AI-based Fraud Score has 98% predictive accuracy. It is not a forensic algorithm based on known bad address lists - it is a predictive model that identifies behavioural patterns associated with fraud before an incident is recorded anywhere.

Every scam follows behavioural patterns stored in on-chain transaction history. ChainAware's models identify these patterns and forecast future behaviour based on past interaction signatures.

Supported Networks¶

Ethereum, BNB Smart Chain, Polygon, Base, TON, TRON, Haqq, and Solana.

AML and Sanctions Monitoring¶

AML and sanctions screening are fully integrated into both the Wallet Auditor and the Fraud Detector - not bolt-on additions. Every audit and every fraud check automatically runs the following:

Sanctions screening - wallets are checked against OFAC SDN, EU Consolidated Sanctions List, and UN Security Council lists in real time
Darknet and mixer exposure - connections to Tornado Cash and other known mixing services, darknet market addresses, and illicit fund clusters
Layering pattern detection - rapid fund cycling, structuring behaviour, and round-number smurfing consistent with AML typologies
Counterparty network analysis - up to N hops through the transaction graph to surface indirect connections to flagged wallets
Known exploit and hack proceeds - flags wallets that received funds traceable to protocol hacks or exit scams

The AML output is structured for compliance use: each flag includes the specific type of exposure, the hop distance, and a timestamped record suitable for audit log storage.

For individuals: the Wallet Auditor and Fraud Detector show AML flags as part of every free report - no account required.

For DeFi protocols: the same signals are available via the REST API and Prediction MCP, with configurable thresholds for ALLOW / FLAG / HOLD / BLOCK pipeline decisions. Covers 16M+ wallet profiles across 8 blockchains.