💳 BIN Database - Offline Checker

Complete offline BIN (Bank Identification Number) database with 9,600+ verified entries.

No API required! Fast, local SQLite database with Python lookup tools.

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🚀 Features

✅ 9,639 BINs - Verified bank identification numbers
✅ 100% Offline - No API keys or internet required
✅ Fast Lookup - SQLite database with indexes
✅ 40+ Countries - Worldwide coverage
✅ Multiple Brands - Visa, Mastercard, Amex, RuPay, Discover, Maestro, UnionPay
✅ Rich Data - Bank name, country, currency, phone, website
✅ JSON Export - Easy integration
✅ Search Options - By BIN, brand, country, bank

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📊 Database Stats

Metric	Count
Total BINs	9,639
Countries	40+
Brands	7 (Visa, MC, Amex, RuPay, Discover, Maestro, UnionPay)
Banks	200+ major banks

Coverage by Country

🇺🇸 USA • 🇮🇳 India • 🇬🇧 UK • 🇨🇦 Canada • 🇯🇵 Japan • 🇧🇷 Brazil • 🇦🇺 Australia • 🇫🇷 France • 🇩🇪 Germany • 🇪🇸 Spain • 🇲🇽 Mexico • 🇷🇺 Russia • 🇨🇳 China • 🇰🇷 South Korea • 🇸🇬 Singapore • 🇦🇪 UAE • 🇸🇦 Saudi Arabia • And 30+ more!

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⚡ Quick Start

1. Clone Repository

git clone https://github.com/DAXXTEAM/bin-database-offline.git
cd bin-database-offline

2. Use Checker

# Lookup a BIN
python3 bin_checker.py 510377

# Search by brand
python3 bin_checker.py --brand mastercard

# Search by country
python3 bin_checker.py --country IN

# Get statistics
python3 bin_checker.py --stats

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📖 Usage Examples

Basic Lookup

$ python3 bin_checker.py 511416

Output:

======================================================================
💳 BIN: 511416
======================================================================
Brand:        MASTERCARD
Type:         DEBIT
Level:        PLATINUM
Bank:         ICICI BANK LIMITED
Country:      India (IN)
Currency:     INR
Valid:        ✅ Yes
======================================================================

Python Integration

from bin_checker import BINChecker

# Initialize
checker = BINChecker()

# Lookup BIN
result = checker.lookup('510377')
print(f"Bank: {result['bank']}")
print(f"Country: {result['country']}")

# Search by country
india_cards = checker.search_by_country('IN')

# Get stats
stats = checker.get_stats()
print(f"Total BINs: {stats['total']:,}")

# Close connection
checker.close()

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🐍 Python Import

from bin_checker import BINChecker

# Context manager (auto-close)
with BINChecker() as checker:
    result = checker.lookup('460223')
    if result:
        print(f"{result['brand']} - {result['bank']}")

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📁 File Structure

bin-database-offline/
├── README.md              # This file
├── bin_checker.py         # Lookup tool
├── bin_database.db        # SQLite database (9,639 BINs)
├── build_database.py      # Database builder
├── test.sh                # Test script
└── .gitignore            # Git ignore rules

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🛠️ Requirements

• Python 3.6+
• SQLite3 (built-in with Python)

No external dependencies! Pure Python stdlib only.

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🔍 Database Schema

CREATE TABLE bins (
    bin TEXT PRIMARY KEY,
    brand TEXT NOT NULL,
    type TEXT NOT NULL,
    level TEXT,
    bank TEXT,
    country TEXT NOT NULL,
    country_code TEXT NOT NULL,
    currency TEXT,
    website TEXT,
    phone TEXT,
    prepaid BOOLEAN DEFAULT 0,
    valid BOOLEAN DEFAULT 1,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

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💳 Supported Brands

• VISA - 2,200+ BINs
• MASTERCARD - 2,200+ BINs
• AMERICAN EXPRESS - 1,600+ BINs
• RUPAY - 1,650+ BINs (India domestic)
• DISCOVER - 900+ BINs
• MAESTRO - 1,600+ BINs
• UNIONPAY - 100+ BINs (China)

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🌍 Major Banks Included

India 🇮🇳

• State Bank of India (SBI)
• HDFC Bank
• ICICI Bank
• Axis Bank
• Kotak Mahindra Bank
• And 50+ more

USA 🇺🇸

• JPMorgan Chase
• Bank of America
• Wells Fargo
• Citibank
• Capital One
• And 100+ more

Worldwide 🌍

• HSBC (UK)
• Barclays (UK)
• Scotiabank (Canada)
• Santander (Spain/Brazil)
• And 100+ international banks

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🔧 Advanced Features

Bulk Lookup

bins = ['510377', '511416', '534444']
for bin_num in bins:
    result = checker.lookup(bin_num)
    print(f"{bin_num}: {result['bank'] if result else 'Not found'}")

Export to CSV

sqlite3 bin_database.db -header -csv "SELECT * FROM bins" > bins_export.csv

Add Custom BINs

import sqlite3
conn = sqlite3.connect('bin_database.db')
cursor = conn.cursor()

cursor.execute('''
    INSERT INTO bins (bin, brand, type, bank, country, country_code, currency, valid)
    VALUES (?, ?, ?, ?, ?, ?, ?, ?)
''', ('999999', 'VISA', 'CREDIT', 'MY BANK', 'India', 'IN', 'INR', 1))

conn.commit()
conn.close()

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📝 License

MIT License - Free to use, modify, and distribute.

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🤝 Contributing

Contributions welcome! To add more BINs:

1. Fork the repository
2. Add BINs to database
3. Test with python3 bin_checker.py --stats
4. Submit pull request

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⚠️ Disclaimer

This database is for educational and development purposes. BIN data is sourced from public information. Always verify critical data with official sources.

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🔗 Resources

• ISO/IEC 7812 - Card numbering standard
• Payment Card Industry - PCI standards

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📧 Contact

Issues? Questions? Open an issue on GitHub!

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🔄 Changelog

v1.1.0 (Latest)

• ✅ Added 563 new BINs
• ✅ Total: 9,639 BINs
• ✅ 40+ countries coverage
• ✅ 200+ banks included

v1.0.0

• 🎉 Initial release
• ✅ 9,093 BINs
• ✅ 4 countries

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⭐ Star this repo if you find it useful!

Made with ❤️ for developers who need offline BIN validation.