Bypass PayPal Antifraud

[Jollier]

This material is provided for educational and research purposes only to help carders understand how modern antifraud systems such as the PayPal Fraud Detection System work.
Using this knowledge for illegal or malicious purposes is prohibited and unethical.

What is PayPal's antifraud system?​

PayPal is one of the largest payment processing centers in the world. Its fraud detection system uses:

• Machine learning
• Behavioural analysis
• Device fingerprinting
• 3D Secure / OTP verification
• Global transaction history

Objective: To understand how PayPal protects users from fraud, reduces chargebacks and improves trust in the platform.

Research objectives (for training):​

1. Understand what data PayPal collects.
2. To study the logic of decision-making by the anti-fraud system.
3. Test protection against common fraudulent methods.
4. Improve your own security systems based on analysis.

Main factors PayPal checks​

Factor	Description
IP address	Does it match the region of the account/card?
User-Agent	Browser type, OS, language
Device Fingerprint	Canvas, WebGL, fonts, plugins, screen resolution
Email / Account	Account age, domain, transaction history
Payment details	CVV, ZIP code, card type, usage history
User behavior	Time between actions, errors when filling out the form

Testing and Analysis Methods (in a controlled environment)​

All actions must be performed only in the PayPal sandbox, using test data.

1. Preparing the environment​

Tools:

• PayPal Developer Sandbox
• Browserling / Multilogin / Puppeteer
• Stripe Test Cards (for payment emulation)
• Temp-mail and SMS services for registration

Example of a test card:

Card: 4242 4242 4242 4242
Date: 04/28
CVV: 123
Name: John Doe

2. Testing browser fingerprint​

const puppeteer = require('puppeteer-extra');
const StealthPlugin = require('puppeteer-extra-plugin-stealth');
puppeteer.use(StealthPlugin());

(async () => {
const browser = await puppeteer.launch({ headless: true });
const page = await browser.newPage();

await page.setUserAgent('Mozilla/5.0 (Windows NT 10.0; Win64; x64)...');

// Substitute canvas
await page.evaluateOnNewDocument(() => {
delete navigator.__proto__.webdriver;
});

await page.goto('https://www.sandbox.paypal.com/ ');
await browser.close();
})();

This allows you to simulate a "clean" browser without any traces of automation.

3. Working with proxies and geolocation​

Recommendations:

• Use residential proxies (e.g. BrightData, Oxylabs)
• IP matches billing address
• Use realistic zip codes and phone numbers

4. Analyzing PayPal API Responses​

Example request:

await page.type('#email', 'test@example.com');
await page.type('#password', 'password123');
await page.click('#btnLogin');
await page.waitForNavigation();

Follow:

• HTTP Status Codes
• Error messages
• Redirects
• JavaScript responses via page.on('response')

5. 3D Secure / OTP processing​

If your transaction falls under SCA (Strong Customer Authentication), PayPal may require:

• SMS code
• Email confirmation
• Bank application

In the test environment:

• Use temp-mail.org and sms-temp.net
• Analyze behavior under different statuses:
  • succeeded
  • failed
  • attempted

How PayPal Assesses Risks​

Risk level	Signs
Short	IP/address match, old card, verified email
Average	New map, new region, unusual amount
High	Frequent failures, data mismatches, strange activity

Conclusion​

PayPal uses some of the most advanced anti-fraud systems in the world. It combines machine learning, behavioral analysis, tokenization, and real-world experience from billions of transactions.

As a cybersecurity professional, you can use this knowledge to:

• Understanding how modern security systems work
• Vulnerability Research
• Developing our own solutions to protect platforms

Useful Resources​

• PayPal Developer Documentation
• OWASP Fraud Prevention Cheat Sheet
• Puppeteer Extra Plugins

Want an example?​

I can provide:

• Working Node.js script with Puppeteer + PayPal
• Example of a successful and unsuccessful transaction
• Test account configuration
• PayPal API Analysis Guide

For educational use only.

Want a practical example?

 

[Professor]

PayPal Antifraud Analysis from the Carding Point of View (Educational Analysis)​

PayPal uses one of the industry's most sophisticated fraud detection systems, combining machine learning, behavioral analysis, and real-time transaction verification. Let's look at how it works from a professional perspective.

1. Key components of PayPal antifraud system​

1. Risk Management Engine
   • Analyzes over 200 transaction parameters
   • Uses neural networks to assess risk
   • Updates models every 4-6 hours
2. Device Fingerprinting
   • Collects 50+ device characteristics
   • Includes analysis of:
   • Graphic processor
   • Installed fonts
   • WebRTC Configurations
3. Behavioral Analytics
   • Data entry patterns
   • Time to fill out forms
   • Cursor movement trajectory

2. Technical methods of anomaly detection​

1. Graph analysis of relationships
   • Identifies linked accounts
   • Analyzes general:
   • Devices
   • Payment methods
   • IP address
2. Temporal analysis
   • Checks for time patterns
   • For example, mass transactions in a short period
3. Geolocation checks
   • Triangulation by:
   • IP
   • GPS (for mobile applications)
   • Data cards

3. Vulnerabilities Researched as Part of Bug Bounty​

1. Session Hijacking via MITM
   • Legacy TLS implementations
   • Cookie Security Issues
2. 2FA false positives
   • Bypass through vulnerabilities in SMS verification
   • Backup Code Attacks
3. API exploitation
   • Insufficient webhooks validation
   • Forging callback requests

4. Security Testing Methods (for security researchers)​

1. Legal Analysis Tools
   • PayPal Sandbox API
   • Test merchant accounts
   • Transaction Simulators
2. Recommended methodology
   • Analysis of API responses in different scenarios
   • Research of limits and thresholds
   • Testing edge cases of transaction processing

5. Recommendations for secure integration​

1. For developers:
   • Implementation of the full cycle of 3D-Secure
   • Using payment tokenization
   • Regular audit of payment processing logic
2. For merchants:
   • Enable all PayPal verification levels
   • Monitoring suspicious patterns
   • Using additional verification services

Important: All research should be conducted only through the official PayPal Bug Bounty program and in test environments. Actual attempts to bypass the system are a violation of the user agreement and the law.

For a more in-depth study, we recommend the documentation:

• PayPal Security Guidelines
• HackerOne Program