Snowflake Analytics Data Protection

Why It Matters

The core goal is to proactively secure every location where analytics data is stored within your Snowflake environment, implementing robust access controls and monitoring before exposure becomes a compliance violation. Preventing analytics data exposure in Snowflake is critical for organizations subject to SOC 2, as it demonstrates your commitment to maintaining customer data confidentiality and implementing proper security controls.

Primary Risk: Unauthorized access to sensitive analytics datasets

Relevant Regulation: SOC 2 Trust Services Criteria

A comprehensive prevention strategy delivers proactive security, ensuring continuous compliance and protecting your organization's most valuable analytical insights.

Prerequisites

Permissions & Roles

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

External Tools

Snowflake CLI or SnowSQL
Cyera DSPM account
API credentials for integrations

Prior Setup

Snowflake account provisioned
Analytics databases and schemas created
Basic RBAC structure established
Network 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) techniques, Cyera automatically identifies sensitive analytics data patterns in Snowflake, applies intelligent data classification, and continuously monitors access patterns to prevent unauthorized exposure before it occurs.

Step-by-Step Guide

Implement role-based access controls

Create granular roles for analytics data access, establish a hierarchy with functional roles, and implement least-privilege principles for all analytics datasets.

CREATE ROLE analytics_reader;
GRANT USAGE ON DATABASE analytics_db TO ROLE analytics_reader;

Configure row-level security policies

In the Cyera portal, navigate to Policies → Data Access → Create Policy. Define row access policies based on user context, department, and data sensitivity levels for your analytics tables.

Enable dynamic data masking

Apply masking policies to sensitive columns in analytics datasets. Configure conditional masking based on user roles and implement column-level security for PII and other sensitive analytics data.

Set up continuous monitoring

Configure real-time alerts for unusual access patterns, implement automated policy enforcement, and establish baseline access patterns for analytics workloads to detect anomalies.

Architecture & Workflow

Snowflake RBAC

Role hierarchy and access control foundation

Row Access Policies

Granular row-level security enforcement

Cyera AI Engine

Continuous monitoring and anomaly detection

Policy Enforcement

Automated remediation and alerting

Security Flow Summary

User Request → RBAC Check → Policy Evaluation → Data Access

Best Practices & Tips

Access Control Strategy

Implement time-based access controls
Use service accounts for automated processes
Regular access reviews and certification

Monitoring & Alerting

Set up query history analysis
Monitor for privilege escalation attempts
Track unusual data export patterns

Common Pitfalls

Over-privileged service accounts
Shared accounts for analytics access
Inadequate monitoring of cloned databases

References & Further Reading

Next Steps

🔍 Detect: Identify analytics data in Snowflake 🔧 Fix: Remediate exposed analytics data