How do organizations audit their payment systems to identify carding vulnerabilities?

[Student]

For educational purposes, I'll describe in detail the process of auditing payment systems to identify carding vulnerabilities, including theoretical foundations, practical approaches, tools, examples, and additional aspects that will help deepen the understanding of this topic. Carding is a type of fraud involving the use of stolen payment card data for unauthorized transactions, so the audit is aimed at minimizing risks and protecting the infrastructure. We'll walk through the process step by step.

1. Understanding carding and its threats​

Carding is a process in which criminals use stolen card data (number, CVV, expiration date, cardholder name) to make purchases, withdraw funds, or test cards. Carding vulnerabilities can occur at the following levels:

• Technical systems: payment gateways, web applications, APIs.
• Processes: weak transaction verification, no two-factor authentication.
• Human factor: phishing, insufficient awareness of employees.
• External factors: data leaks on the darknet, weak protection from partners.

The purpose of the audit is to identify weaknesses in the payment system that could be exploited by carders and implement measures to eliminate them.

2. Preparation for the audit​

Before commencing an audit, the organization must:

• Determine the audit scope: What systems, applications, processes, and data will be audited? For example, an online store website, a payment gateway, or a mobile app.
• Assemble a team: Includes internal specialists (IT, information security) and, if necessary, external auditors (e.g., PCI DSS certified).
• Review regulatory requirements:
  • PCI DSS: A cardholder data security standard that applies to anyone who processes, stores, or transmits card data.
  • Local legislation (for example, in Russia - Federal Law 152-FZ "On Personal Data").
  • International standards such as GDPR (in the EU) or CCPA (in California).
• Create an audit plan: Determine the stages, deadlines, tools and risk areas.

3. Main stages of the audit​

3.1. Compliance Audit​

• PCI DSS: This is the basic standard for organizations working with payment cards. An audit includes checking 12 requirements, such as:
  • Data encryption: Is TLS 1.2 or higher used for data transfer? Is card data stored encrypted?
  • Access Control: Who has access to card data? Is the principle of least privilege used?
  • Monitoring and Logging: Are system access logs maintained? Is there an intrusion detection system (IDS/IPS)?
  • Vulnerability Management: Are systems regularly updated and tested for vulnerabilities?
• Example: A company checks whether it stores CVV codes (which is prohibited by PCI DSS) and whether it uses tokenization to replace card numbers with unique tokens.
• Other standards: If the organization operates in the EU, compliance with the GDPR is checked (e.g. minimizing the storage of personal data of clients).

3.2. Technical audit (Vulnerability Assessment and Penetration Testing)​

• Vulnerability Scanning:
  • Tools such as Nessus, Qualys, OpenVAS are used to automatically detect vulnerabilities in networks, servers and applications.
  • Known vulnerabilities such as CVE (Common Vulnerabilities and Exposures) are checked, including outdated software or weak configurations.
• Pentest:
  • Manual or automated penetration testing is performed:
    • Web Applications: Checks for vulnerabilities such as SQL injection, XSS, CSRF (cross-site request forgery).
    • Payment gateway API: Protection against data interception attacks (e.g. MITM - Man-in-the-Middle) is checked.
    • Social engineering: Simulating phishing attacks to test employee reactions.
  • Example tool: Burp Suite for analyzing HTTP requests and testing web applications.
• Example: Carders can exploit weak payment form validation to enter fake data. Penetration testing verifies how the system responds to incorrect or suspicious requests.

3.3. Analysis of transactions and anti-fraud systems​

• Fraud detection systems:
  • Platforms such as Kount, Sift, Riskifiedare used, which analyze transactions in real time based on:
    • Geographical compliance (for example, a transaction from the US when the card is registered in Russia).
    • Behavioral patterns (multiple payment attempts in a short period of time).
    • Devices and IP addresses (use of VPN, Tor or suspicious devices).
  • Machine learning algorithms detect anomalies such as unusually large amounts or mass card testing.
• 3D-Secure: Checks whether additional authentication protocols (Verified by Visa, Mastercard SecureCode, Mir Accept) are implemented. The absence of 3D-Secure increases the risk of fraud.
• Example: An online store notices a series of small transactions from different cards to a single IP address. The anti-fraud system should automatically block such attempts.

3.4 Code and Configuration Audit​

• Static code analysis:
  • Payment application code is checked for vulnerabilities such as:
    • Incorrect handling of user input.
    • Lack of protection against injections (SQL, commands).
  • Tools such as SonarQube, Checkmarx, or Fortify are used.
• Server configuration:
  • It is checked that servers use secure protocols (TLS 1.2+, prohibition of outdated SSL).
  • Ensure that databases do not contain unencrypted card data.
  • The use of tokenization (replacing card data with tokens that are useless to attackers) is being checked.
• Example: An API vulnerability could allow carders to send fake transaction authorization requests. A code audit reveals such errors.

3.5. Simulating Carder Attacks​

• Controlled tests are conducted simulating the actions of carders:
  • Attempts to enter stolen card details to purchase goods or withdraw funds.
  • Testing the system for carding attacks (multiple transaction attempts with different cards).
  • Checking the system's response to suspicious actions (for example, automatic blocking after several unsuccessful attempts).
• Example: A company can use a test database of cards (provided by payment systems) to test anti-fraud filters.

3.6. Process and human factors testing​

• Staff training:
  • We check whether employees know how to recognize phishing, suspicious calls or emails.
  • Trainings on social engineering are conducted.
• Process audit:
  • Chargeback procedures are being checked, as carders often use chargebacks to withdraw money.
  • Employee access to payment systems is analyzed (for example, whether a call center operator has access to card data).
• Example: An employee who received a phishing email may accidentally give up access to the payment system's admin panel. An audit reveals training deficiencies.

3.7. Darknet and Data Leak Monitoring​

• Services such as Have I Been Pwned, Visa Threat Intelligence, or Dark Web Monitoring are used to check if customer data has been leaked to the dark web.
• It is checked whether stolen card data is used in the company's transactions.
• Example: If a database of cards associated with a company is discovered on the dark web, it signals a possible leak.

4. Tools and technologies​

The following tools are used to conduct the audit:

• Vulnerability scanners: Nessus, Qualys, OpenVAS, Acunetix.
• Penetration testing tools: Burp Suite, Metasploit, OWASP ZAP.
• SIEM systems (for log monitoring): Splunk, QRadar, ArcSight.
• Anti-fraud platforms: Kount, Sift, Forter, Signifyd, Riskified.
• Code analysis tools: SonarQube, Checkmarx, Fortify.
• Darknet Monitoring: Recorded Future, Flashpoint.

5. Sample audit scenario​

Situation: An online store wants to test its payment system for carding vulnerabilities.

1. Preparation: A team is assembled (internal information security specialist, external PCI DSS auditor).
2. Scan: Used by Nessus to check servers for vulnerabilities (eg outdated Apache).
3. Pentest: Burp Suite detects XSS vulnerability in payment form allowing malicious script injection.
4. Transaction analysis: Kount's system detects anomalies - 10 transactions from one IP per minute.
5. Code review: SonarQube finds that map data is stored in the database without tokenization.
6. Simulation: Test transactions with counterfeit cards show that the system does not block suspicious attempts.
7. Recommendations: Implement 3D-Secure, fix XSS, use tokenization, train employees.

6. Recommendations for preventing carding​

• Technical measures:
  • Implement 3D-Secure for all transactions.
  • Use tokenization and do not store card data.
  • Set up monitoring systems (SIEM) and anti-fraud.
• Process measures:
  • Limit the number of attempts to enter card data.
  • Implement a strict return policy.
• Training:
  • Conduct cybersecurity training regularly.
  • Simulate phishing attacks to test employee reactions.
• Cooperation:
  • Work with banks and payment systems to exchange fraud data.
  • Connect to databases of stolen cards (e.g. TCAB).

7. Legal and regulatory aspects​

• PCI DSS: Failure to comply may result in fines and loss of card acceptance privileges.
• GDPR: Customer data breaches can result in large fines.
• Incident response: The organization must have a plan to respond to breaches, including notifying customers and regulators within 72 hours (under GDPR).

8. Conclusion​

Auditing payment systems to protect against carding is a comprehensive process encompassing technical, process, and human aspects. Regular audits, the implementation of modern technologies (3D-Secure, tokenization, anti-fraud systems), and staff training significantly reduce risks. For in-depth study, I recommend reviewing materials from OWASP, the PCI Security Standards Council, and specialized cybersecurity courses.

If you'd like, I can provide specific case studies or cover a specific aspect (such as SIEM setup or code analysis). Let me know what you're interested in!