Databricks PCI Data Detection
Learn how to detect PCI data in Databricks environments. Follow step-by-step guidance for PCI-DSS compliance.
Why It Matters
The core goal is to identify every location where payment card industry (PCI) data is stored within your Databricks environment, so you can remediate unintended exposures before they become breaches. Scanning for PCI data in Databricks is a priority for organizations subject to PCI-DSS requirements, as it helps you prove you've discovered and accounted for all sensitive payment data—mitigating the risk of exposure and potential fines up to $100,000 per month.
A thorough scan delivers immediate visibility into cardholder data environments (CDE), laying the foundation for automated policy enforcement and ongoing compliance with PCI-DSS requirements 3.1 and 3.2.
Prerequisites
Permissions & Roles
- Databricks admin or service principal
- catalogs/read, schemas/read, tables/read privileges
- Ability to install Databricks CLI or Terraform
External Tools
- Databricks CLI
- Cyera DSPM account
- API credentials
Prior Setup
- Databricks workspace provisioned
- Unity Catalog enabled
- CLI authenticated
- Networking rules configured
Introducing Cyera
Cyera is a modern Data Security Posture Management (DSPM) platform that discovers, classifies, and continuously monitors your sensitive data across cloud services. Using advanced AI and machine learning models including Named Entity Recognition (NER) and pattern matching algorithms, Cyera automatically identifies PCI data such as credit card numbers, CVV codes, and payment processor tokens in your Databricks environment. This ensures you stay ahead of accidental exposures and meet PCI-DSS audit requirements in real time.
Step-by-Step Guide
Ensure Unity Catalog is enabled in your account and create a service principal with the minimum required privileges. Enable PCI-DSS compliance profile if processing regulated payment data.
In the Cyera portal, navigate to Integrations → DSPM → Add new. Select Databricks, provide your host URL and service principal details, then define the scan scope. Configure PCI-specific detection rules including credit card numbers, expiration dates, and CVV patterns.
Configure webhooks or streaming exports to push scan results into your SIEM or Security Hub. Link findings to existing ticketing systems like Jira or ServiceNow. Set up alerts for high-confidence PCI data discoveries.
Review the initial detection report, prioritize tables with large volumes of payment card data, and adjust detection rules to reduce false positives. Schedule recurring scans to maintain visibility and ensure continuous compliance with PCI-DSS requirements.
Architecture & Workflow
Databricks Unity Catalog
Source of metadata for tables and files
Cyera Connector
Pulls metadata and samples data for classification
Cyera Back-end
Applies PCI detection models and risk scoring
Reporting & Remediation
Dashboards, alerts, and compliance playbooks
Data Flow Summary
Best Practices & Tips
Performance Considerations
- Start with incremental or scoped scans
- Use sampling for very large transaction tables
- Tune sample rates for speed vs coverage
Tuning Detection Rules
- Maintain allowlists for test credit card numbers
- Adjust confidence thresholds for Luhn algorithm validation
- Match rules to your PCI scope boundaries
Common Pitfalls
- Forgetting historical payment data in archived tables
- Over-scanning development environments with synthetic data
- Neglecting to validate PCI-DSS compliance profile settings