Recalling Snowflake Data Masking Policies for Secure and Compliant Access

Snowflake can hide your most sensitive data. It can also reveal it if you need. The core is data masking—rules that control exactly what a query returns, depending on who runs it. When you recall Snowflake data masking, you’re talking about reinstating, reviewing, or restoring masking policies that dictate access at a fine-grained level.

Snowflake’s data masking works through Masking Policies tied to columns. These policies filter data on query execution without storing separate copies. Role-based access means the same query can deliver masked or unmasked data depending on the executing role. It’s clean. It’s fast. It’s secure.

To recall a Snowflake data masking policy, you need to know its name and the schema where it’s applied. The process is simple:

1. Use SHOW MASKING POLICIES to list all policies.
2. Identify the target.
3. Review its definition with DESCRIBE MASKING POLICY policy_name.
4. Apply or reapply it using ALTER TABLE ... SET MASKING POLICY ... on the right column.

Recalling a previously removed or adjusted policy ensures compliance stays intact. Audit logs in Snowflake’s Account Usage schema give you the trail—who changed what, and when. This is critical for regulated environments or incident response. Restoring the right policy closes exposure fast.

The difference between a live mask and stored masked data matters. Live masking scales with your queries and roles without duplicating tables. Recalling a policy is about returning that live mask to the column, not rebuilding datasets.

Get this wrong and sensitive rows go raw. Get it right and your Snowflake warehouse will only show what's meant to be seen—while keeping the rest invisible.

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