GCP PII Detection
Learn how to detect personally identifiable information (PII) 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 personally identifiable information is stored within your Google Cloud Platform environment, so you can remediate unintended exposures before they become breaches. Scanning for PII in GCP is a priority for organizations subject to GDPR, as it helps you prove you've discovered and accounted for all sensitive personal data assets—mitigating the risk of data exposure through misconfigured storage buckets, databases, or compute instances.
A thorough scan delivers immediate visibility into PII across Cloud Storage, BigQuery, Cloud SQL, and Compute Engine, laying the foundation for automated policy enforcement and ongoing compliance.
Prerequisites
Permissions & Roles
- Project Owner or Editor role
- Cloud DLP Admin or DLP User role
- BigQuery Data Viewer (if scanning BigQuery)
- Storage Object Viewer (if scanning Cloud Storage)
External Tools
- Google Cloud CLI (gcloud)
- Cyera DSPM account
- Service account credentials
Prior Setup
- GCP project provisioned
- Sensitive Data Protection API enabled
- Service account created and authenticated
- Network access 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 and Named Entity Recognition (NER) models, Cyera automatically identifies PII patterns in your GCP environment—from email addresses and phone numbers to more complex personal identifiers. This ensures you stay ahead of accidental exposures and meet GDPR compliance requirements in real time.
Step-by-Step Guide
Enable the Sensitive Data Protection API and create a service account with appropriate IAM roles for accessing your data sources.
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 across Cloud Storage, BigQuery, and other data stores.
Configure webhooks or streaming exports to push scan results into your SIEM or Security Operations Center. Link findings to existing ticketing systems like Jira or ServiceNow for automated remediation workflows.
Review the initial detection report, prioritize datasets with large volumes of PII, and adjust detection rules to reduce false positives. Schedule recurring scans to maintain visibility across your dynamic GCP environment.
Architecture & Workflow
GCP Data Sources
Cloud Storage, BigQuery, Cloud SQL, Compute Engine
Cyera Connector
Pulls metadata and samples data for classification
Cyera AI Engine
Applies NER models and PII detection algorithms
Reporting & Remediation
Dashboards, alerts, and compliance reports
Data Flow Summary
Best Practices & Tips
Performance Considerations
- Start with smaller projects or specific datasets
- Use sampling for very large BigQuery tables
- Configure regional scanning to optimize costs
Tuning Detection Rules
- Maintain allowlists for test or synthetic data
- Adjust confidence thresholds for PII types
- Configure custom regex patterns for organization-specific identifiers
Common Pitfalls
- Forgetting Cloud Storage buckets in different regions
- Over-scanning temporary compute instance disks
- Neglecting to monitor new projects or datasets