FraudLabs Pro

Overview

FraudLabs Pro provides an application programming interface (API) for real-time fraud detection and prevention, primarily targeting e-commerce businesses and online payment gateways. Founded in 2013, the service integrates into existing transaction workflows to assess risk for orders, registrations, and user activities. Its core function involves analyzing data points such as IP address geolocation, proxy detection, email validation, transaction velocity, and payment instrument details to generate a fraud risk score for each event. This score helps businesses automate decisions on whether to accept, review, or reject a transaction, aiming to minimize financial losses from fraudulent purchases and reduce chargeback rates.

The system is designed to identify various types of fraudulent behaviors, including credit card fraud, identity theft, and suspicious account sign-ups. By leveraging a combination of rule-based logic and machine learning algorithms, FraudLabs Pro can adapt to evolving fraud patterns. Developers can integrate the FraudLabs Pro API into their applications using various software development kits (SDKs) for languages like PHP, Python, and Node.js, as well as pre-built plugins for popular e-commerce platforms such as Shopify, WooCommerce, and Magento. This flexibility supports both custom-built systems and off-the-shelf e-commerce solutions, enabling a broad range of businesses to implement fraud prevention measures without extensive custom development. The API documentation provides extensive examples and guides for integrating fraud detection into payment workflows, ensuring clear implementation paths for developers.

For businesses concerned with data privacy, FraudLabs Pro maintains compliance with regulations such as GDPR. This ensures that personal data processed for fraud screening adheres to established privacy standards. The service is particularly beneficial for online retailers, subscription services, and digital goods providers who experience high volumes of transactions and are susceptible to various forms of online fraud, including triangulation fraud and friendly fraud. By providing a comprehensive risk assessment, it allows merchants to refine their fraud prevention strategies and improve overall operational efficiency. The developer experience is characterized by straightforward integration, with well-documented API references and code examples available on the official FraudLabs Pro developer portal.

Key features

• Real-time Transaction Screening: Automatically evaluates incoming transactions for fraud indicators using a combination of rules and machine learning, providing a fraud score instantly.
• Geolocation and IP Analysis: Identifies the geographic location of the user's IP address and detects the use of proxies, VPNs, or TOR networks, which can be indicators of fraud.
• Email Validation: Checks email addresses for validity, domain reputation, and common disposable email services to prevent fraud associated with temporary or fake accounts.
• Device Fingerprinting: Collects and analyzes device-specific attributes to identify repeat fraudulent users, even if they change IP addresses or payment methods.
• Blacklist/Whitelist Management: Allows businesses to manually add specific IP addresses, email addresses, or countries to a blacklist (deny access) or whitelist (allow access) based on their risk assessment.
• Customizable Rules: Provides tools to create and manage custom fraud prevention rules tailored to specific business needs and risk tolerances.
• Notification System: Configurable alerts and notifications for suspicious transactions, enabling manual review when automated rules flag an order.
• Multi-platform support: Offers SDKs and plugins for various programming languages and e-commerce platforms, including PHP integration for FraudLabs Pro and specific integrations for platforms like Shopify and WooCommerce.

Pricing

FraudLabs Pro offers a tiered pricing model that scales with the number of queries processed per month, starting with a free tier and progressing to paid plans for higher volumes. The pricing structure is designed to accommodate businesses of various sizes, from startups to large enterprises. All paid plans include access to the same core fraud detection features, with differences primarily in query volume and customer support levels.

Pricing accurate as of 2026-05-28. For the most current pricing details, please refer to the official FraudLabs Pro pricing page.

Common integrations

FraudLabs Pro provides extensive integration options through its API and pre-built plugins for various e-commerce platforms and programming languages.

• Shopify: Direct plugin for integrating fraud detection into Shopify stores, available on the Shopify App Store.
• WooCommerce: Official plugin for WordPress-based e-commerce sites, enabling fraud screening for orders.
• Magento: Extension available for Magento 1 and Magento 2 platforms to enhance transaction security.
• OpenCart: Integration module for OpenCart e-commerce solutions.
• PHP: SDK and example code for integrating the FraudLabs Pro PHP API client into custom PHP applications.
• Python: SDK and code examples for Python applications, facilitating custom fraud detection logic.
• Node.js: JavaScript SDK for server-side Node.js environments.
• Java: Library and documentation for Java-based enterprise applications.
• Ruby: Gem available for Ruby on Rails and other Ruby projects.

Alternatives

Businesses seeking fraud detection solutions may consider several alternatives to FraudLabs Pro, each offering distinct features and integration approaches.

• Sift: A comprehensive digital trust and safety platform that leverages machine learning to detect and prevent fraud across the entire customer journey, including payment fraud, account takeover, and content abuse. Sift's approach emphasizes real-time decision-making and a global data network.
• Signifyd: Specializes in e-commerce fraud prevention with a chargeback guarantee model, meaning they cover the cost of chargebacks on approved orders. Signifyd uses machine learning to automate fraud decisions for merchants.
• Riskified: Focuses on e-commerce fraud and chargeback prevention, also offering a chargeback guarantee. Riskified's platform employs AI and a network of merchant data to identify legitimate customers and block fraudulent orders.

Getting started

To begin using FraudLabs Pro, developers typically sign up for an account, obtain an API key, and then integrate the API into their application. The following example demonstrates a basic transaction check using the Python SDK. This code snippet shows how to send transaction details to the FraudLabs Pro API and interpret the fraud assessment response. Before running, ensure the FraudLabs Pro Python SDK is installed (e.g., pip install FraudLabsPro).

import fraudlabspro

# Your FraudLabs Pro API Key
API_KEY = "YOUR_API_KEY"

# Initialize the client with your API key
fraudlabspro.configure(API_KEY)

def check_transaction_fraud(ip_address, email, country_code, amount, currency, user_order_id):
    try:
        response = fraudlabspro.check(
            ip=ip_address,
            email=email,
            country=country_code,
            amount=amount,
            currency=currency,
            order_id=user_order_id
        )

        if response:
            print("FraudLabs Pro Response:")
            print(f"  Fraud Score: {response.get('fraudlabspro_score')}")
            print(f"  Fraud Status: {response.get('fraudlabspro_status')}")
            print(f"  IP Country: {response.get('ip_country')}")
            print(f"  Is Proxy: {response.get('is_proxy')}")
            print(f"  Risk Level: {response.get('fraudlabspro_risk_level')}")
            print(f"  Message: {response.get('fraudlabspro_message')}")
            return response
        else:
            print("No response from FraudLabs Pro API.")
            return None
    except Exception as e:
        print(f"An error occurred: {e}")
        return None

# Example usage:
if __name__ == "__main__":
    # Replace with actual transaction data
    ip_addr = "203.0.113.45" # Example IP address
    user_email = "[email protected]"
    country = "US"
    transaction_amount = 129.99
    transaction_currency = "USD"
    order_id = "ORD123456789"

    fraud_check_result = check_transaction_fraud(ip_addr, user_email, country, transaction_amount, transaction_currency, order_id)

    if fraud_check_result:
        score = fraud_check_result.get('fraudlabspro_score')
        status = fraud_check_result.get('fraudlabspro_status')

        if score and int(score) > 80: # Example threshold
            print("\nAction: High risk transaction, consider manual review or rejection.")
        elif status == "DENY":
            print("\nAction: Transaction denied by FraudLabs Pro rules.")
        elif status == "APPROVE":
            print("\nAction: Transaction approved.")
        else:
            print("\nAction: Transaction requires further assessment.")

This Python script initiates a fraud check by sending relevant transaction parameters to the FraudLabs Pro API. The response includes a fraud score, a status (e.g., APPROVE, DENY, REVIEW), and various risk indicators. Developers can then use these details to implement conditional logic within their payment processing or order management systems. For more detailed integration guides, including specific examples for other programming languages and e-commerce platforms, refer to the FraudLabs Pro API reference documentation.