Snowflake Customer Data Protection

Learn how to prevent exposure of customer data in Snowflake environments. Follow step-by-step guidance for GDPR compliance.

data exposure

GDPR

snowflake

Why It Matters

The core goal is to implement comprehensive protection mechanisms for customer data within your Snowflake environment, preventing unauthorized access and ensuring compliance before breaches occur. Proactive customer data protection in Snowflake is essential for organizations subject to GDPR, as it helps you maintain privacy by design and demonstrate accountability for personal data processing.

Primary Risk: Data exposure through misconfigured access controls

Relevant Regulation: GDPR General Data Protection Regulation

A robust prevention strategy delivers proactive security, ensuring customer data remains protected through automated policy enforcement and continuous monitoring.

Prerequisites

Permissions & Roles

  • Snowflake ACCOUNTADMIN or SECURITYADMIN role
  • USAGE privileges on relevant databases and schemas
  • Ability to create and manage row access policies

External Tools

  • Snowflake CLI or SnowSQL
  • Cyera DSPM account
  • API credentials for automation

Prior Setup

  • Snowflake account provisioned
  • Customer data classification completed
  • User roles and hierarchies defined
  • Network security 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 and Natural Language Processing (NER) models, Cyera automatically identifies customer data patterns in Snowflake, enabling proactive protection through intelligent policy recommendations and real-time risk assessment for GDPR compliance.

Step-by-Step Guide

1
Configure row-level security policies

Create row access policies to restrict customer data access based on user context and business requirements. Define policies that align with your data classification schema.

CREATE ROW ACCESS POLICY customer_data_policy AS (user_region VARCHAR) RETURNS BOOLEAN ->

2
Implement dynamic data masking

In the Cyera portal, configure masking policies for customer PII columns. Set up conditional masking rules that preserve data utility while protecting sensitive information from unauthorized users.

3
Enable continuous monitoring

Configure Cyera's AI-powered monitoring to detect policy violations and unauthorized access attempts. Set up alerts for suspicious query patterns or privilege escalations that could expose customer data.

4
Validate protection effectiveness

Test access controls with different user personas, verify masking policies are working correctly, and establish regular audits to ensure ongoing protection. Monitor Cyera's risk dashboard for compliance insights.

Architecture & Workflow

Snowflake Access Control

RBAC, row-level security, and masking policies

Cyera AI Engine

Continuously monitors access patterns and risks

Policy Engine

Enforces protection rules and compliance standards

Monitoring & Alerts

Real-time notifications and compliance reporting

Protection Flow Summary

Classify Data → Apply Policies → Monitor Access → Alert & Respond

Best Practices & Tips

Access Control Design

  • Implement principle of least privilege
  • Use role hierarchies for scalable management
  • Regular access reviews and certifications

Data Masking Strategy

  • Format-preserving encryption for testing
  • Context-aware masking rules
  • Performance optimization for large datasets

Common Pitfalls

  • Over-permissive default roles
  • Forgetting to mask derived tables
  • Inadequate monitoring of admin activities

References & Further Reading

Next Steps

🔍 Detect: Identify existing customer data exposures 🔧 Fix: Remediate discovered customer data issues