Dynamic data masking end-to-end example - Amazon Redshift
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Dynamic data masking end-to-end example

The following is an end-to-end example showing how you can create and attach masking policies to a column. These policies let users access a column and see different values, depending on the degree of obfuscation in the policies attached to their roles. You must be a superuser or have the sys:secadmin role to run this example.

Creating a masking policy

First, create a table and populate it with credit card values.

--create the table CREATE TABLE credit_cards ( customer_id INT, credit_card TEXT ); --populate the table with sample values INSERT INTO credit_cards VALUES (100, '4532993817514842'), (100, '4716002041425888'), (102, '5243112427642649'), (102, '6011720771834675'), (102, '6011378662059710'), (103, '373611968625635') ; --run GRANT to grant permission to use the SELECT statement on the table GRANT SELECT ON credit_cards TO PUBLIC; --create two users CREATE USER regular_user WITH PASSWORD '1234Test!'; CREATE USER analytics_user WITH PASSWORD '1234Test!'; --create the analytics_role role and grant it to analytics_user --regular_user does not have a role CREATE ROLE analytics_role; GRANT ROLE analytics_role TO analytics_user;

Next, create a masking policy to apply to the analytics role.

--create a masking policy that fully masks the credit card number CREATE MASKING POLICY mask_credit_card_full WITH (credit_card VARCHAR(256)) USING ('000000XXXX0000'::TEXT); --create a user-defined function that partially obfuscates credit card data CREATE FUNCTION REDACT_CREDIT_CARD (credit_card TEXT) RETURNS TEXT IMMUTABLE AS $$ import re regexp = re.compile("^([0-9]{6})[0-9]{5,6}([0-9]{4})") match = regexp.search(credit_card) if match != None: first = match.group(1) last = match.group(2) else: first = "000000" last = "0000" return "{}XXXXX{}".format(first, last) $$ LANGUAGE plpythonu; --create a masking policy that applies the REDACT_CREDIT_CARD function CREATE MASKING POLICY mask_credit_card_partial WITH (credit_card VARCHAR(256)) USING (REDACT_CREDIT_CARD(credit_card)); --confirm the masking policies using the associated system views SELECT * FROM svv_masking_policy; SELECT * FROM svv_attached_masking_policy;

Attaching a masking policy

Attach the masking policies to the credit card table.

--attach mask_credit_card_full to the credit card table as the default policy --all users will see this masking policy unless a higher priority masking policy is attached to them or their role ATTACH MASKING POLICY mask_credit_card_full ON credit_cards(credit_card) TO PUBLIC; --attach mask_credit_card_partial to the analytics role --users with the analytics role can see partial credit card information ATTACH MASKING POLICY mask_credit_card_partial ON credit_cards(credit_card) TO ROLE analytics_role PRIORITY 10; --confirm the masking policies are applied to the table and role in the associated system view SELECT * FROM svv_attached_masking_policy; --confirm the full masking policy is in place for normal users by selecting from the credit card table as regular_user SET SESSION AUTHORIZATION regular_user; SELECT * FROM credit_cards; --confirm the partial masking policy is in place for users with the analytics role by selecting from the credit card table as analytics_user SET SESSION AUTHORIZATION analytics_user; SELECT * FROM credit_cards;

Altering a masking policy

The following section shows how to alter a dynamic data masking policy.

--reset session authorization to the default RESET SESSION AUTHORIZATION; --alter the mask_credit_card_full policy ALTER MASKING POLICY mask_credit_card_full USING ('00000000000000'::TEXT); --confirm the full masking policy is in place after altering the policy, and that results are altered from '000000XXXX0000' to '00000000000000' SELECT * FROM credit_cards;

Detaching and dropping a masking policy

The following section shows how to detach and drop masking policies by removing all dynamic data masking policies from the table.

--reset session authorization to the default RESET SESSION AUTHORIZATION; --detach both masking policies from the credit_cards table DETACH MASKING POLICY mask_credit_card_full ON credit_cards(credit_card) FROM PUBLIC; DETACH MASKING POLICY mask_credit_card_partial ON credit_cards(credit_card) FROM ROLE analytics_role; --drop both masking policies DROP MASKING POLICY mask_credit_card_full; DROP MASKING POLICY mask_credit_card_partial;