GCP Financial Records Detection
Learn how to detect financial records in Google Cloud Platform environments. Follow step-by-step guidance for PCI DSS compliance.
Why It Matters
The core goal is to identify every location where financial records are stored within your Google Cloud Platform environment, so you can remediate unintended exposures before they become breaches. Scanning for financial data in GCP is a priority for organizations subject to PCI DSS, as it helps you prove you've discovered and accounted for all sensitive financial assets—mitigating the risk of data exposure through misconfigured storage or overly permissive access controls.
A thorough scan delivers immediate visibility, laying the foundation for automated policy enforcement and ongoing compliance.
Prerequisites
Permissions & Roles
- GCP Project Owner or Editor role
- BigQuery Data Viewer permissions
- Cloud Storage Object Viewer access
External Tools
- Google Cloud CLI (gcloud)
- Cyera DSPM account
- Service account credentials
Prior Setup
- GCP project provisioned
- BigQuery datasets configured
- Cloud Storage buckets accessible
- IAM policies 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. By leveraging advanced AI techniques including Named Entity Recognition (NER) and machine learning pattern matching, Cyera automatically identifies financial records in GCP by analyzing data patterns, column names, and content structure to detect credit card numbers, bank account information, and other financial data types in real time.
Step-by-Step Guide
Create a service account with the minimum required privileges for BigQuery and Cloud Storage access, then generate and securely store the JSON key file.
In the Cyera portal, navigate to Integrations → DSPM → Add new. Select Google Cloud Platform, provide your project ID and service account credentials, then define the scan scope to include BigQuery datasets and Cloud Storage buckets.
Configure webhooks or streaming exports to push scan results into your SIEM or Security Command Center. Link findings to existing ticketing systems like Jira or ServiceNow for remediation workflows.
Review the initial detection report, prioritize datasets with large volumes of financial records, and adjust detection rules to reduce false positives. Schedule recurring scans to maintain visibility across your GCP environment.
Architecture & Workflow
BigQuery & Cloud Storage
Source of structured and unstructured financial data
Cyera Connector
Pulls metadata and samples data for classification
Cyera AI Engine
Applies NER and ML models for financial data detection
Reporting & Remediation
Dashboards, alerts, and compliance reports
Data Flow Summary
Best Practices & Tips
Performance Considerations
- Start with incremental or scoped scans
- Use sampling for very large BigQuery tables
- Configure scan frequency based on data volatility
Tuning Detection Rules
- Maintain allowlists for test financial data
- Adjust confidence thresholds for credit card detection
- Configure custom patterns for internal account formats
Common Pitfalls
- Missing Cloud SQL databases with financial data
- Over-scanning archived or backup datasets
- Forgetting to scan Firestore collections