Considerations when using dynamic data masking - Amazon Redshift
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Considerations when using dynamic data masking

When using dynamic data masking, consider the following:

  • When querying objects created from tables, such as views, users will see results based on their own masking policies, not the policies of the user who created the objects. For example, a user with the analyst role querying a view created by a secadmin would see results with masking policies attached to the analyst role.

  • To prevent the EXPLAIN command from potentially exposing sensitive masking policy filters, only users with the SYS_EXPLAIN_DDM permission can see masking policies applied in EXPLAIN outputs. Users don't have the SYS_EXPLAIN_DDM permission by default.

    The following is the syntax for granting the permission to a role.

    GRANT EXPLAIN MASKING TO ROLE rolename

    For more information about the EXPLAIN command, see EXPLAIN.

  • Users with different roles can see differing results based on the filter conditions or join conditions used. For example, running a SELECT command on a table using a specific column value will fail if the user running the command has a masking policy applied that obfuscates that column.

  • DDM policies must be applied ahead of any predicate operations, or projections. Masking polices can include the following:

    • Low cost constant operations such as converting a value to null

    • Moderate cost operations such as HMAC hashing

    • High cost operations such as calls to external Lambda user defined functions

    As such, we recommend that you use simple masking expressions when possible.

  • You can use DDM policies for roles with row-level security policies, but note that RLS policies are applied before DDM. A dynamic data masking expression won't be able to read a row that was protected by RLS. For more information about RLS, see Row-level security.

  • When using the COPY command to copy from parquet to protected target tables, you should explicitly specify columns in the COPY statement. For more information about mapping columns with COPY, see Column mapping options.

  • DDM policies can't attach to the following relations:

    • System tables and catalogs

    • External tables

    • Datasharing tables

    • Materialized views

    • Cross-DB relations

    • Temporary tables

    • Correlated queries

  • DDM policies can contain lookup tables. Lookup tables can be present in the USING clause. The following relation types can’t be used as lookup tables:

    • System tables and catalogs

    • External tables

    • Datasharing tables

    • Views, materialized views, and late-binding views

    • Cross-DB relations

    • Temporary tables

    • Correlated queries

    Following is an example of attaching a masking policy to a lookup table.

    --Create a masking policy referencing a lookup table CREATE MASKING POLICY lookup_mask_credit_card WITH (credit_card TEXT) USING ( CASE WHEN credit_card IN (SELECT credit_card_lookup FROM credit_cards_lookup) THEN '000000XXXX0000' ELSE REDACT_CREDIT_CARD(credit_card) END ); --Provides access to the lookup table via a policy attached to a role GRANT SELECT ON TABLE credit_cards_lookup TO MASKING POLICY lookup_mask_credit_card;
  • You can't attach a masking policy that would produce an output incompatible with the target column's type and size. For example, you can’t attach a masking policy that outputs a 12 character long string to a VARCHAR(10) column. Amazon Redshift supports the following exceptions:

    • A masking policy with the input type INTN can be attached to a policy with size INTM as long as M < N. For example, a BIGINT (INT8) input policy can be attached to a smallint (INT4) column.

    • A masking policy with the input type NUMERIC or DECIMAL can always be attached to a FLOAT column.

  • DDM policies can't be used with data sharing. If the datashare's data producer attaches a DDM policy to a table in the datashare, the table becomes inaccessible to users from the data consumer who are trying to query the table. Tables with DDM policies attached can't be added to a datashare.

  • You can't query relations that have attached DDM policies if your values for any of the following configuration options don't match the default value of the session:

    • enable_case_sensitive_super_attribute

    • enable_case_sensitive_identifier

    • downcase_delimited_identifier

    Consider resetting your session’s configuration options if you attempt to query a relation with a DDM policy attached and see the message "DDM protected relation does not support session level config on case sensitivity being different from its default value."

  • When your provisioned cluster or serverless namespace has any dynamic data masking policies, the following commands are blocked for regular users:

    ALTER <current_user> SET enable_case_sensitive_super_attribute/enable_case_sensitive_identifier/downcase_delimited_identifier

    When you create DDM policies, we recommend that you change the default configuration option settings for regular users to match the session’s configuration option settings at the time the policy was created. Superusers and users with the ALTER USER privilege can do this by using parameter group settings or the ALTER USER command. For information about parameter groups, see Amazon Redshift parameter groups in the Amazon Redshift Management Guide. For information about the ALTER USER command, see ALTER USER.

  • Views and late-binding views with attached DDM policies can't be replaced by regular users using the CREATE VIEW command. To replace views or LBVs with DDM policies, first detach any DDM policies attached to them, replace the views or LBVs, and reattach the policies. Superusers and users with the sys:secadmin permission can use CREATE VIEW on views or LBVs with DDM policies without detaching the policies.

  • Views with attached DDM policies can't reference system tables and views. Late-binding views can reference system tables and views.

  • Late-binding views with attached DDM policies can't reference nested data in data lakes, such as JSON documents.

  • Late-binding views can't have DDM policies attached if that late-binding view is referenced by any view.

  • DDM policies attached to late-binding views are attached by column name. At query time, Amazon Redshift validates that all masking policies attached to the late-binding view have been applied successfully, and that the late-binding view's output column type matches the types in the attached masking policies. If the validation fails, Amazon Redshift returns an error for the query.

  • You can use customized session context variables when creating DDM policies. The following example sets session context variables for a DDM policy.

    -- Set a customized context variable. SELECT set_config('app.city', 'XXXX', FALSE); -- Create a MASKING policy using current_setting() to get the value of a customized context variable. CREATE MASKING POLICY city_mask WITH (city VARCHAR(30)) USING (current_setting('app.city')::VARCHAR(30)); -- Attach the policy on the target table to one or more roles. ATTACH MASKING POLICY city_mask ON tickit_users_redshift(city) TO ROLE analyst, ROLE dbadmin;

    For details on how to set and retrieve customized session context variables, go to SET, SET_CONFIG, SHOW, CURRENT_SETTING, and RESET. For more information on modifying the server configuration in general, go to Modifying the server configuration.

    Important

    When using session context variables within DDM policies, the security policy is reliant on the user or role that invokes the policy. Be careful to avoid security vulnerabilities when using session context variables in DDM policies.