GCP Customer Data Detection
Learn how to detect customer data in Google Cloud Platform environments. Follow step-by-step guidance for GDPR compliance.
Why It Matters
The core goal is to identify every location where customer information is stored within your Google Cloud Platform environment, so you can remediate unintended exposures before they become breaches. Scanning for customer data in GCP is a priority for organizations subject to GDPR, as it helps you prove you've discovered and accounted for all sensitive customer assets—mitigating the risk of data exposure through misconfigured access controls.
A thorough scan delivers immediate visibility, laying the foundation for automated policy enforcement and ongoing compliance.
Prerequisites
Permissions & Roles
- Project Owner or Security Admin role
- BigQuery Data Viewer permissions
- Cloud Storage Object Viewer access
External Tools
- Google Cloud SDK
- Cyera DSPM account
- Service account key
Prior Setup
- GCP project provisioned
- BigQuery datasets configured
- Cloud Storage buckets accessible
- IAM policies reviewed
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 pattern matching, Cyera automatically identifies customer data in GCP services like BigQuery, Cloud Storage, and Cloud SQL, ensuring you stay ahead of accidental exposures and meet GDPR audit requirements in real time.
Step-by-Step Guide
Create a service account with the minimum required permissions to scan BigQuery datasets, Cloud Storage buckets, and other data stores containing customer information.
In the Cyera portal, navigate to Integrations → DSPM → Add new. Select Google Cloud Platform, provide your service account credentials and project details, then define the scan scope across BigQuery, Cloud Storage, and other relevant services.
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 tracking.
Review the initial detection report, prioritize datasets with large volumes of customer PII, and adjust detection rules to reduce false positives. Schedule recurring scans to maintain visibility across your GCP environment.
Architecture & Workflow
GCP Data Sources
BigQuery, Cloud Storage, Cloud SQL metadata
Cyera Connector
Pulls metadata and samples data for classification
Cyera AI Engine
Applies NER models and pattern detection
Reporting & Remediation
Dashboards, alerts, and playbooks
Data Flow Summary
Best Practices & Tips
Performance Considerations
- Start with high-priority projects and datasets
- Use table sampling for very large BigQuery tables
- Configure regional scanning to minimize latency
Tuning Detection Rules
- Maintain allowlists for test environments
- Adjust confidence thresholds for customer data
- Focus on GDPR-relevant data categories
Common Pitfalls
- Missing Cloud Storage objects without proper naming
- Over-scanning development or staging environments
- Forgetting to rotate service account keys regularly