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Datasets:
Codatta
/
Crypto-Address-Annotation-10K

Tasks:
Token Classification
Modalities:
Text
Formats:
csv
Languages:
English
Size:
10K - 100K
Tags:
cryptocurrency
blockchain
address-labeling
security
entity-recognition
Libraries:
Datasets
pandas
License:
Dataset card Data Studio Files
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metadata
language:
  - en
license: openrail
tags:
  - cryptocurrency
  - blockchain
  - address-labeling
  - security
  - entity-recognition
pretty_name: Codatta Crypto Address Annotations
size_categories:
  - 1K<n<10K
task_categories:
  - token-classification

Codatta Crypto Address Annotations (Sample)

Overview

This dataset is a 10,000-row sample of the comprehensive Codatta Crypto Address Annotations database. The full database serves as a massive repository of over 500 million labeled address pairs across multiple blockchains.

The data provides critical metadata aimed at solving the problem of fragmented and siloed blockchain information. It includes entity names, functional categories (e.g., Exchanges, DeFi, Scam), and risk assessments. The dataset is curated through a unique hybrid approach that bridges crowdsourced intelligence with standardized open protocols:

  • Codatta Platform: Aggregates data from a decentralized data intelligence network, verified by a community of contributors.
  • Microscope Protocol: Utilizes an open-source initiative for collaborative crypto address labeling to ensure high fidelity and standardization.

Dataset Contents

The dataset contains structured metadata for crypto addresses. The specific data fields included in this sample are:

  • chain (string): The blockchain network (e.g., bitcoin, ethereum).
  • address (string): The specific wallet or smart contract address.
  • name (string): The specific label name (e.g., "Binance Deposit Address").
  • entity (string): The entity that owns or controls the address (e.g., "Binance").
  • category (string): Functional classification (e.g., CEX, DeFi, Scam).
  • source (string): The origin of the label, such as ground_truth, external, heuristics, or machine_learning.

Key Statistics

While this repository provides a sample for testing, the complete Codatta database covers a massive scale of on-chain entities. Below is the distribution of the full 517.61 Million labeled pairs.

1. Distribution by Chain

(Total labeled pairs: 517,609,906)

Chain Address Count
Bitcoin 185,818,811
Polygon 129,251,435
Ethereum 107,420,551
BSC (BNB Chain) 61,043,196
Tron 22,055,631
Optimism 4,926,779
Arbitrum 3,488,054
Avalanche 3,369,625
Base 233,495

2. Distribution by Category (Top Categories)

Category Address Count
Smart Contract 235,023,302
Exchange 187,716,225
Scam 24,261,860
Gambling 21,677,685
Ransom 17,991,759
DeFi User 16,825,002
Bridging User 11,516,923
DEX User 7,286,609
ERC20 Token 5,442,026
Mixer 5,186,762
Wallet 2,724,811
FIAT 2,145,036
Darknet 2,110,659
Sanctioned 1,101,861

Usage

This 10k sample is released publicly to foster research, demonstrate data quality, and allow developers to test data integration.

  • Research & Testing: Use this sample to evaluate the schema, label accuracy, and coverage for tasks like token classification or entity recognition.
  • Commercial & Advanced Use: Users interested in accessing the full dataset (500M+ labels) for commercial applications, advanced analytics, or security integration should contact the Codatta team directly.

License and Open-Source Details