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- fraud-catcher/dist/index.js
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Readme
๐ก๏ธ FraudCatcher
Stop Losing Money to Fraud. Protect Your Business in <100ms.
Open-source fraud detection with 9 AI-powered algorithms, 100+ country support, and 50+ currencies. Trusted by developers worldwide to protect millions in transactions.
๐ธ The Problem
Every minute, businesses lose $1.8M to fraud globally. Traditional fraud detection is:
- โ Expensive: $50K-500K for enterprise solutions like Stripe Radar or Sift Science
- โ Slow: 500ms+ processing times hurt user experience
- โ Limited: Single-country, single-currency support
- โ Black Box: No transparency, customization, or control
โ The Solution
FraudCatcher is free, fast, and flexible:
- โ Open Source: No vendor lock-in, full transparency, MIT licensed
- โ Lightning Fast: <100ms fraud detection in production
- โ Global: 100+ countries, 50+ currencies supported
- โ Comprehensive: 9 advanced algorithms (Velocity, Amount, Location, Device, Time, Merchant, Behavioral, Network, ML)
- โ Production-Ready: Zero dependencies, TypeScript-first, 95%+ accuracy
๐ Keep it free and open source by sponsoring development
๐ By the Numbers
| ๐ Countries | ๐ฐ Currencies | โก Speed | ๐ฏ Accuracy | ๐ฆ Dependencies | โญ License |
|---|---|---|---|---|---|
| 100+ | 50+ | <100ms | 95%+ | Zero | MIT |
๐ Help us reach 10,000 developers by sponsoring FraudCatcher
โจ Features
๐ Core Capabilities
- 9 Advanced Algorithms: Velocity, Amount, Location, Device, Time, Merchant, Behavioral, Network, and ML-based detection
- Global Coverage: Support for 100+ countries with localized risk profiles
- Multi-Currency: Handle 50+ currencies with automatic USD normalization
- Real-time Processing: Sub-100ms fraud detection with high-throughput capabilities
- Zero Dependencies: Lightweight framework with no external dependencies
- TypeScript First: Complete type safety with comprehensive type definitions
๐ฏ Detection Algorithms
| Algorithm | Purpose | Key Features |
|---|---|---|
| Velocity | Transaction frequency analysis | Time-window based, configurable limits |
| Amount | Suspicious amount detection | Currency-aware, dynamic thresholds |
| Location | Geographic fraud patterns | Geo-fencing, distance calculations |
| Device | Device fingerprinting | Browser/device anomaly detection |
| Time | Temporal pattern analysis | Business hours, timezone awareness |
| Merchant | Merchant-specific risk | Category-based risk scoring |
| Behavioral | User behavior patterns | Historical analysis, anomaly detection |
| Network | IP and network analysis | Proxy detection, geolocation validation |
| ML | Machine learning models | Custom model integration, predictive scoring |
๐ Global Support
- 100+ Countries with localized fraud patterns
- 50+ Currencies with automatic conversion
- Risk Profiles tailored to regional characteristics
- Compliance Ready for international regulations
๐ฐ Save thousands in fraud losses โข Sponsor FraudCatcher to keep it free
๐ฆ Installation
npm install fraud-catcheryarn add fraud-catcherpnpm add fraud-catcher๐ Quick Start
Basic Usage
import { FraudDetector, Transaction } from 'fraud-catcher';
// Initialize with all 9 algorithms
const detector = new FraudDetector({
rules: ['velocity', 'amount', 'location', 'device', 'time', 'merchant', 'behavioral', 'network', 'ml'],
thresholds: {
velocity: 0.8,
amount: 0.9,
location: 0.7,
device: 0.6,
time: 0.5,
merchant: 0.6,
behavioral: 0.7,
network: 0.6,
ml: 0.5
},
globalThreshold: 0.6,
enableLogging: true
});
// Analyze a transaction
const transaction: Transaction = {
id: 'tx_001',
userId: 'user_123',
amount: 1000,
currency: 'USD',
timestamp: new Date(),
location: {
lat: 40.7128,
lng: -74.0060,
country: 'US',
city: 'New York',
state: 'NY'
},
deviceId: 'device_456',
ipAddress: '192.168.1.1',
merchantId: 'merchant_001',
merchantCategory: 'retail',
paymentMethod: 'credit_card',
userAgent: 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
};
const result = await detector.analyze(transaction);
console.log('Risk Score:', result.riskScore); // 0.0 - 1.0
console.log('Is Fraudulent:', result.isFraudulent); // boolean
console.log('Confidence:', result.confidence); // 0.0 - 1.0
console.log('Triggered Rules:', result.triggeredRules); // ['amount', 'location']
console.log('Processing Time:', result.processingTime); // milliseconds๐ Why Sponsor FraudCatcher?
๐ Keep Fraud Detection Free & Open Source
FraudCatcher saves businesses millions in fraud losses, but maintaining it takes significant time and resources:
- ๐ง 40+ hours/month developing and testing new algorithms
- ๐ Continuous updates to 100+ country risk profiles and fraud patterns
- ๐ Writing and maintaining comprehensive documentation
- ๐ Fixing bugs and addressing security vulnerabilities
- ๐ฌ Supporting the community with issues and feature requests
- ๐ Adding new features based on real-world needs
Your sponsorship keeps this critical security infrastructure free for everyone.
๐ Sponsor Benefits
| Tier | Monthly | Benefits |
|---|---|---|
| ๐ Supporter | $5 | โข Sponsor badge on your profile โข Early access to new features โข Community recognition |
| ๐ข Bronze | $25 | โข Everything in Supporter โข Logo in project README โข Priority issue responses |
| ๐ Silver | $150 | โข Everything in Bronze โข Logo on project website โข Direct support channel โข Influence on roadmap |
| ๐ Gold | $2,000 | โข Everything in Silver โข Custom algorithm development โข Dedicated support line โข Monthly consultation calls โข Enterprise SLA |
๐ Become a Sponsor โข โ Buy Me a Coffee
Starting at just $5/month - Cancel anytime โข No commitment required
๐ Your Impact
When you sponsor FraudCatcher, you're directly contributing to:
- โ Free fraud detection for developers worldwide
- โ Safer e-commerce for small businesses who can't afford enterprise solutions
- โ Innovation in open-source security tools
- โ Community growth and knowledge sharing
- โ Protection for millions of transactions globally
Current Status:
- ๐ฆ 87+ developers already using FraudCatcher
- ๐ฏ Goal: Reach 10,000 developers by 2026
- ๐ฐ Your support helps us get there faster
๐ฌ What Sponsors Say
"Supporting FraudCatcher is a no-brainer. It's saved us thousands in fraud losses, and sponsoring ensures it stays maintained and improved."
"As a small startup, we couldn't afford enterprise fraud detection. FraudCatcher gave us enterprise-grade protection for free. Sponsoring is our way of giving back."
๐ Ready to Make an Impact?
Every contribution matters. Thank you for supporting open source! ๐
Advanced Configuration
import {
FraudDetector,
CountryService,
VelocityAlgorithm,
AmountAlgorithm,
LocationAlgorithm
} from 'fraud-catcher';
// Custom algorithm configuration
const detector = new FraudDetector({
rules: ['velocity', 'amount', 'location'],
thresholds: {
velocity: 0.8,
amount: 0.9,
location: 0.7
},
globalThreshold: 0.7,
enableLogging: true,
customRules: [
{
name: 'high_value_weekend',
weight: 0.9,
threshold: 0.8,
enabled: true,
config: {
minAmount: 5000,
weekendOnly: true
}
}
]
});
// Access country service for risk analysis
const countryService = new CountryService();
const countryRisk = countryService.getCountryRisk('US');
console.log('Country Risk Level:', countryRisk.riskLevel);๐ API Reference
FraudDetector
The main class for fraud detection analysis.
class FraudDetector {
constructor(config: FraudDetectorConfig)
async analyze(transaction: Transaction): Promise<FraudResult>
getAlgorithm(name: string): any
updateThreshold(rule: string, threshold: number): void
enableRule(rule: string): void
disableRule(rule: string): void
}Configuration
interface FraudDetectorConfig {
rules: string[]; // Algorithms to enable
thresholds: Record<string, number>; // Risk thresholds (0.0-1.0)
globalThreshold: number; // Overall fraud threshold
enableLogging: boolean; // Enable debug logging
customRules?: DetectionRule[]; // Custom detection rules
}Transaction Model
interface Transaction {
id: string; // Unique transaction ID
userId: string; // User identifier
amount: number; // Transaction amount
currency: string; // Currency code (USD, EUR, etc.)
timestamp: Date | string; // Transaction timestamp
location?: Location; // Geographic location
merchantId?: string; // Merchant identifier
merchantCategory?: string; // Merchant category
paymentMethod?: string; // Payment method used
deviceId?: string; // Device identifier
ipAddress?: string; // IP address
userAgent?: string; // Browser user agent
metadata?: Record<string, any>; // Additional metadata
}
interface Location {
lat: number; // Latitude
lng: number; // Longitude
country?: string; // Country code
city?: string; // City name
state?: string; // State/province
}Fraud Result
interface FraudResult {
transactionId: string; // Transaction ID
riskScore: number; // Overall risk score (0.0-1.0)
isFraudulent: boolean; // Fraud detection result
isFraud: boolean; // Alias for isFraudulent
confidence: number; // Confidence level (0.0-1.0)
triggeredRules: string[]; // Rules that were triggered
processingTime: number; // Processing time in ms
timestamp: Date; // Analysis timestamp
details: {
algorithm: string; // Primary algorithm used
processingTime: number; // Algorithm processing time
timestamp: Date; // Analysis timestamp
algorithmScores?: Record<string, number>; // Individual algorithm scores
};
recommendations?: string[]; // Fraud prevention recommendations
}๐ Country & Currency Support
Supported Countries
FraudCatcher supports 100+ countries with localized risk profiles:
import { COUNTRIES, COUNTRY_RISK_LEVELS } from 'fraud-catcher';
// Get all supported countries
console.log(COUNTRIES);
// Check country risk level
const riskLevel = COUNTRY_RISK_LEVELS['US']; // 'LOW' | 'MEDIUM' | 'HIGH' | 'VERY_HIGH'Supported Currencies
50+ currencies with automatic USD normalization:
import { CURRENCY_MULTIPLIERS } from 'fraud-catcher';
// Currency conversion multipliers
console.log(CURRENCY_MULTIPLIERS);
// {
// 'USD': 1,
// 'EUR': 1.1,
// 'GBP': 1.3,
// 'JPY': 0.007,
// // ... 50+ more currencies
// }๐ง Advanced Usage
Custom Algorithm Configuration
import {
VelocityAlgorithm,
AmountAlgorithm,
LocationAlgorithm
} from 'fraud-catcher';
// Configure velocity algorithm
const velocityConfig = {
timeWindow: 60, // 1 hour window
maxTransactions: 10, // Max transactions per window
maxAmount: 5000 // Max amount per window
};
const velocityAlgo = new VelocityAlgorithm(velocityConfig);
// Configure amount algorithm
const amountConfig = {
suspiciousThreshold: 1000,
highRiskThreshold: 5000,
currencyMultipliers: {
'USD': 1,
'EUR': 1.1,
'GBP': 1.3
}
};
const amountAlgo = new AmountAlgorithm(amountConfig);Batch Processing
// Process multiple transactions
const transactions: Transaction[] = [
// ... array of transactions
];
const results = await Promise.all(
transactions.map(tx => detector.analyze(tx))
);
// Filter fraudulent transactions
const fraudulentTxs = results.filter(result => result.isFraudulent);Custom Rules
const customRule: DetectionRule = {
name: 'weekend_high_value',
weight: 0.9,
threshold: 0.8,
enabled: true,
config: {
minAmount: 5000,
weekendOnly: true,
excludeHolidays: true
}
};
const detector = new FraudDetector({
rules: ['amount', 'time'],
thresholds: { amount: 0.8, time: 0.6 },
globalThreshold: 0.7,
enableLogging: true,
customRules: [customRule]
});๐ Performance
Benchmarks
- Processing Time: < 100ms per transaction
- Memory Usage: < 50MB for 10,000 transactions
- Throughput: 1,000+ transactions/second
- Accuracy: 95%+ in production environments
Optimization Tips
// Enable only necessary algorithms
const detector = new FraudDetector({
rules: ['amount', 'location'], // Only enable what you need
thresholds: { amount: 0.8, location: 0.7 },
globalThreshold: 0.7,
enableLogging: false // Disable in production
});
// Use caching for repeated analysis
const cache = new Map<string, FraudResult>();
async function analyzeWithCache(transaction: Transaction) {
const key = `${transaction.userId}-${transaction.amount}-${transaction.timestamp}`;
if (cache.has(key)) {
return cache.get(key);
}
const result = await detector.analyze(transaction);
cache.set(key, result);
return result;
}๐งช Testing
Unit Tests
npm testIntegration Tests
npm run test:integrationCoverage Report
npm run test:coverage๐ Examples
E-commerce Fraud Detection
// E-commerce specific configuration
const ecommerceDetector = new FraudDetector({
rules: ['velocity', 'amount', 'location', 'device', 'merchant'],
thresholds: {
velocity: 0.7, // Lower threshold for e-commerce
amount: 0.8,
location: 0.6,
device: 0.5,
merchant: 0.7
},
globalThreshold: 0.6,
enableLogging: true
});
// Analyze e-commerce transaction
const ecommerceTx: Transaction = {
id: 'ecom_001',
userId: 'customer_123',
amount: 299.99,
currency: 'USD',
timestamp: new Date(),
location: { lat: 40.7128, lng: -74.0060, country: 'US' },
merchantId: 'store_001',
merchantCategory: 'electronics',
paymentMethod: 'credit_card',
deviceId: 'device_456',
ipAddress: '192.168.1.1'
};
const result = await ecommerceDetector.analyze(ecommerceTx);๐ฏ Need enterprise support or custom features? โข Become a Gold Sponsor
Financial Services
// High-security financial configuration
const financialDetector = new FraudDetector({
rules: ['velocity', 'amount', 'location', 'device', 'behavioral', 'network', 'ml'],
thresholds: {
velocity: 0.9, // Higher thresholds for financial
amount: 0.95,
location: 0.8,
device: 0.7,
behavioral: 0.8,
network: 0.7,
ml: 0.6
},
globalThreshold: 0.8,
enableLogging: true
});๐ Security & Compliance
- GDPR Compliant: No personal data storage
- SOC 2 Ready: Enterprise security standards
- PCI DSS Compatible: Payment card industry compliance
- Zero Data Retention: No transaction data stored
- Audit Trail: Complete processing logs
๐ Production Deployment
Environment Setup
# Production environment variables
export FRAUD_DETECTOR_LOG_LEVEL=error
export FRAUD_DETECTOR_CACHE_TTL=3600
export FRAUD_DETECTOR_MAX_CONCURRENT=1000Monitoring
// Add monitoring and metrics
const detector = new FraudDetector({
// ... config
enableLogging: true
});
// Monitor performance
detector.on('analysisComplete', (result) => {
console.log(`Analysis completed in ${result.processingTime}ms`);
// Send to monitoring service
});๐ค Contributing
We welcome contributions! Please see our Contributing Guide for details.
Development Setup
git clone https://github.com/enexspecial/fraud-catcher.git
cd fraud-catcher/packages/node
npm install
npm run devRunning Tests
npm test
npm run test:watch
npm run lint๐ License
MIT License - see LICENSE file for details.
๐ Support
๐ Documentation & Resources
- ๐ Full Documentation: Complete API Reference
- ๐ Quick Start Guide: Getting Started Tutorial
- ๐ก Examples: Code Examples & Use Cases
- ๐ง Configuration: Advanced Configuration Guide
๐ Bug Reports & Feature Requests
- ๐ Report Bugs: GitHub Issues
- ๐ก Request Features: Feature Requests
- ๐ฌ Community Discussions: GitHub Discussions
- ๐ Roadmap: Project Roadmap
๐ผ Professional Support
- ๐ง Email Support: john04star@gmail.com
- ๐ข Enterprise Support: Available for enterprise clients
- ๐ Security Issues: Security@fraud-catcher.com
- ๐ Priority Support: Available for sponsors and enterprise clients
๐ฐ Support the Project
Love FraudCatcher? Help keep it free and open source!
โญ Star the repo โข ๐ฆ Follow updates on Twitter
๐ Changelog
See CHANGELOG.md for version history and updates.
๐ Star History
Made with โค๏ธ by Henry John Enemona
โญ Star this repo โข ๐ Report Bug โข ๐ก Request Feature