Entity Attribution
How the engine identifies known counterparties.
Entity attribution is the process of mapping observed counterparty addresses to known entities — exchanges, protocols, mixers, sanctioned addresses, and known public figures.
CredScore uses a hardcoded entity label database covering hundreds of addresses across major categories: top centralized exchanges (Coinbase, Binance, Kraken, etc.), DEX routers (Uniswap, SushiSwap, Curve), bridges (Stargate, Wormhole, Synapse), lending protocols (Aave, Compound, MakerDAO), staking (Lido, Rocket Pool), NFT marketplaces (OpenSea, Blur, X2Y2), and known bad actors (OFAC sanctioned addresses, Lazarus Group, recent hack proceeds).
Each label has a category (cex, dex, bridge, mixer, protocol, treasury), a confidence level (high, medium, low), and a rationale.
Attribution affects scoring in multiple ways:
Recognized counterparties improve confidence. The engine knows what these addresses are, so it has more context.
Categories influence the entity context signal. Exchange and DeFi context generally normalizes routing complexity. Mixer or sanctions context increases risk.
Known-good entities (Vitalik Buterin, Ethereum Foundation) get a positive boost and have their structural pattern review suppressed — the engine treats high-confidence identity attribution as a strong positive context signal.
Unattributed counterparties are treated cautiously. Wallets with very low attribution get a "weak attribution coverage" flag and reduced confidence.