GCP Employee Data Detection
Learn how to detect employee 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 employee information is stored within your Google Cloud Platform environment, so you can remediate unintended exposures before they become breaches. Scanning for employee data in GCP is a priority for organizations subject to GDPR, as it helps you prove you've discovered and accounted for all sensitive HR assets—mitigating the risk of data exposure through misconfigurations 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
- Cloud Storage Admin or Viewer permissions
- BigQuery Data Viewer permissions
- DLP API Admin role
External Tools
- Google Cloud CLI (gcloud)
- Cyera DSPM account
- Service account credentials
Prior Setup
- GCP project with billing enabled
- Sensitive Data Protection API enabled
- Service account 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 employee data patterns in GCP resources including Cloud Storage buckets, BigQuery datasets, and Cloud SQL instances, ensuring you stay ahead of GDPR compliance requirements and data exposure risks in real time.
Step-by-Step Guide
Enable the Sensitive Data Protection API and create a service account with the minimum required privileges for scanning Cloud Storage, BigQuery, and other data repositories.
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 Cloud Storage buckets, BigQuery datasets, and Cloud SQL instances.
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 for automated remediation workflows.
Review the initial detection report, prioritize resources with large volumes of employee PII, and adjust detection rules to reduce false positives. Schedule recurring scans to maintain visibility across your GCP environment.
Architecture & Workflow
GCP Data Sources
Cloud Storage, BigQuery, Cloud SQL, and Firestore
Cyera Connector
Pulls metadata and samples data for classification
Cyera AI Engine
Applies NER models and risk scoring algorithms
Reporting & Remediation
Dashboards, alerts, and compliance playbooks
Data Flow Summary
Best Practices & Tips
Performance Considerations
- Start with specific projects or regions
- Use sampling for very large BigQuery tables
- Configure rate limits to avoid API quotas
Tuning Detection Rules
- Maintain allowlists for test environments
- Adjust confidence thresholds by data type
- Match rules to your GDPR risk tolerance
Common Pitfalls
- Forgetting Cloud SQL and Firestore instances
- Over-scanning temporary or staging buckets
- Neglecting to rotate service account keys