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- ---
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- license: openrail
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ language:
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+ - en
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+ license: openrail
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+ tags:
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+ - cryptocurrency
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+ - blockchain
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+ - address-labeling
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+ - security
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+ - entity-recognition
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+ pretty_name: Codatta Crypto Address Annotations
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+ size_categories:
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+ - 1K<n<10K
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+ task_categories:
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+ - token-classification
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+ ---
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+
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+ # Codatta Crypto Address Annotations (Sample)
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+
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+ ## Dataset Summary
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+
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+ This repository contains a **10,000-row sample** of the Codatta Crypto Address Annotations database. The full dataset comprises over **500 million** labeled address pairs across multiple blockchains.
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+
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+ The data provides critical metadata such as entity names, categories (e.g., Exchanges, DeFi, Scam), and risk levels. It is curated through a unique hybrid approach, combining high-quality community contributions from the **Codatta** platform and collaborative data from the **Microscope Protocol**.
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+
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+ By bridging crowdsourced intelligence with standardized open protocols, this dataset aims to solve the problem of fragmented and siloed blockchain metadata.
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+
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+
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+ ## Data Sources & Protocols
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+
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+ The high fidelity of this dataset is achieved through two primary sources:
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+
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+ 1. **Codatta Platform:** Data aggregated from Codatta's decentralized data intelligence network, verified by the contributor community.
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+
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+ 2. **Microscope Protocol:** We utilize the Microscope Protocol, an open-source initiative for collaboratively labeling crypto addresses.
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+ * **Official Website:** [https://microscopeprotocol.net/](https://microscopeprotocol.net/)
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+ * **Context:** [Microscope: Protocol for Collaboratively Labeling Crypto Addresses (Coinbase Blog)](https://www.coinbase.com/blog/microscope-protocol-for-collaboratively-labeling-crypto-addresses)
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+
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+ ## Full Dataset Statistics
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+
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+ While this repository provides a 10k sample for testing and research, our complete database covers a massive scale of on-chain entities. Below is the distribution of our full **517.61 Million** labeled pairs.
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+
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+ ### 1. Distribution by Chain
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+ *Total labeled (chain, address) pairs: 517,609,906*
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+
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+ | Chain | Address Count |
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+ | :--- | :--- |
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+ | **Bitcoin** | 185,818,811 |
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+ | **Polygon** | 129,251,435 |
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+ | **Ethereum** | 107,420,551 |
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+ | **BSC** (BNB Chain) | 61,043,196 |
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+ | **Tron** | 22,055,631 |
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+ | **Optimism** | 4,926,779 |
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+ | **Arbitrum** | 3,488,054 |
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+ | **Avalanche** | 3,369,625 |
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+ | **Base** | 233,495 |
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+ | *Others (Litecoin, Solana, etc.)* | < 2,000 |
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+
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+ ### 2. Distribution by Category (Top Categories)
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+
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+ | Category | Address Count |
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+ | :--- | :--- |
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+ | **Smart Contract** | 235,023,302 |
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+ | **Exchange** | 187,716,225 |
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+ | **Scam** | 24,261,860 |
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+ | **Gambling** | 21,677,685 |
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+ | **Ransom** | 17,991,759 |
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+ | **DeFi User** | 16,825,002 |
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+ | **Bridging User** | 11,516,923 |
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+ | **DEX User** | 7,286,609 |
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+ | **ERC20 Token** | 5,442,026 |
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+ | **Mixer** | 5,186,762 |
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+ | **Wallet** | 2,724,811 |
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+ | **FIAT** | 2,145,036 |
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+ | **Darknet** | 2,110,659 |
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+ | **Sanctioned** | 1,101,861 |
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+
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+ *(Table truncated for brevity; other categories include Lending User, Liquid Staking, NFT, etc.)*
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+
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+ ## Access to Full Dataset
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+ We are releasing this **10k sample** publicly to foster research and demonstrate data quality.
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+ **If you are interested in accessing the full dataset (500M+ labels) for commercial use, advanced analytics, or security integration, please contact us.**
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+
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+ ## Dataset Structure
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+
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+ ### Data Fields
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+ * **`chain`** (string): The blockchain network (e.g., `bitcoin`, `ethereum`).
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+ * **`address`** (string): The wallet or contract address.
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+ * **`name`** (string): Specific label name (e.g., "Binance Deposit Address").
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+ * **`entity`** (string): The entity owning the address (e.g., "Binance").
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+ * **`category`** (string): Functional classification (e.g., `CEX`, `DeFi`, `Scam`). See full list at [Microscope Protocol Categories](https://docs.microscopeprotocol.xyz/onboarding/data/categories).
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+ * **`source`** (string): Origin of the label (`ground_truth`, `external`, `heuristics`, `machine_learning`).