💳PCI DSS 3.4critical

Render cardholder data unreadable

Description

Stored cardholder data must be rendered unreadable (encryption, hashing, truncation).

⚠️ Risk Impact

Readable cardholder data stolen in a breach leads to fraud and regulatory penalties.

🔧 Remediation

Encrypt all stored cardholder data. EchelonGraph verifies encryption on databases and storage.

💀 Real-World Attack Scenario

An e-commerce company stored full PANs in a PostgreSQL database without encryption. A SQL injection vulnerability allowed an attacker to dump the entire cardholder data table — 1.2M unencrypted card numbers with expiry dates and CVVs. The card numbers were immediately usable for fraud.

💰 Cost of Non-Compliance

Storing readable PANs = immediate PCI DSS non-compliance. Card brand fines: $50K-$500K. Fraud liability: merchant assumes all fraudulent charges. Average cost: $3.8M. Potential loss of payment processing privileges.

📋 Audit Questions

  • 1.Where is cardholder data stored?
  • 2.What methods render cardholder data unreadable?
  • 3.Are encryption keys separate from the data they protect?
  • 4.Is full PAN ever logged or stored in plaintext?

🎯 MITRE ATT&CK Mapping

T1005 — Data from Local SystemT1505.001 — SQL Stored Procedures

⚡ Common Pitfalls

  • Encrypting the database but logging full PANs in application logs
  • Using reversible encryption without proper key management
  • Full PANs stored in backup files, exports, or error logs

📈 Business Value

Cardholder data encryption eliminates the most damaging outcome of a payment system breach — direct financial fraud. It's the difference between a security incident and a catastrophic data breach.

⏱️ Effort Estimate

Manual

8-16 hours to audit all cardholder data storage locations

With EchelonGraph

EchelonGraph verifies encryption on all databases and storage

🔗 Cross-Framework References

SOC2-CC6.1ISO27001-A.10.1.1

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