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    Secure and control access to application data

    Parameterized secure views provide row-level data security and access control by filtering query results based on application user identity.

    This tutorial describes how to set up parameterized secure views in Cloud SQL, configure database roles and privileges to restrict access to base tables, and verify data security. The examples provided in this document are for demonstration purposes only.

    What are parameterized secure views?

    As a general best practice, your application should run using a service account with the minimal required access to your database. For example, if your application shouldn't write to your database, it should use a role with read-only access. You should configure these access controls at the database level.

    When your application needs more granular security than standard database-level access permits, you can use parameterized secure views to make sure that users view only their authorized data.

    Using parameterized secure views provides two main benefits:

    • Dynamic row-level security: Filters queries using end-user identifiers so users access only their authorized data regardless of query phrasing.
    • Simplified role management: Uses a single shared database role for all application users instead of managing separate database roles for each individual.

    Objectives

    • Create parameterized secure views with named view parameters.
    • Create the database role that is used by the application to connect to the database and access parameterized secure views.
    • Grant the new role permissions to the parameterized secure views and revoke access to the base tables.
    • Connect using the new role and verify that the restricted tables can't be accessed.
    • Run queries on the parameterized secure views using the execute_parameterized_query() function or using the QueryData API.

    Costs

    In this document, you use the following billable components of Google Cloud:

    To generate a cost estimate based on your projected usage, use the pricing calculator .

    New Google Cloud users might be eligible for a free trial .

    To avoid continued billing, delete the resources you created when you finish the tasks in this document. For more information, see Clean up .

    Before you begin

    Before you create parameterized secure views, complete the following prerequisites.

    Enable billing and required APIs

    1. In the Google Cloud console, select a project.

      Go to project selector

    2. Make sure that billing is enabled for your Google Cloud project.

    3. Enable the Cloud APIs necessary to create and connect to Cloud SQL.

      1. Enable the API

      2. In the Confirm project step, click Next to confirm the name of the project you are going to make changes to.

      3. In the Enable APIs step, click Enable to enable the following:

        • Cloud SQL for PostgreSQL API
        • Knowledge Catalog API

    Create and connect to a database

    1. Create an instance .
    2. Connect to your instance and create a database .

    Prepare your environment

    To prepare for running queries on a parameterized secure view, set up the database, database roles, the parameterized_views extension, and the application schema.

    Enable the database flag

    Enable the cloudsql.enable_parameterized_views database flag, which loads the required extension libraries. For more information, see Configure an instance's database flags .

    Set up the database

    • Create a database called database for the application data and parameterized secure views. For more information, see Create a database .

    Create database roles, the extension, and the application schema

    1. In the Google Cloud console, go to the Cloud SQL page.

      Go to Cloud SQL

    2. Select an instance from the list.

    3. In the navigation menu, click Cloud SQL Studio.

    4. Sign in to Studiousing postgres authentication.

    5. Click Authenticate. The Explorer pane displays a list of the objects in your database.

    6. Click New SQL editor tabor New tabto open a new tab.

    7. To use parameterized views, create the parameterized_views extension in your database:

        -- Requires parameterized_views.enabled set to true 
 CREATE 
  
 EXTENSION 
  
 parameterized_views 
 ;

      When the extension is created, the database also creates a schema named parameterized_views so that the APIs are contained in that schema's namespace and so that those APIs don't conflict with existing APIs.

    8. Sign in as a user with superuser privileges, such as the built-in postgres user.

    9. Create a new database role for executing queries against parameterized secure views. This is an Cloud SQL role that the application uses to connect and sign into the database to execute queries with limited access to public functions or objects to the minimal required set.

        CREATE 
  
 ROLE 
  
 psv_user 
  
 WITH 
  
 LOGIN 
  
 PASSWORD 
  
 '...' 
 ;

      For more information, see CREATE USER .

    10. Connect as the administrative user.

        SET 
  
 role 
  
 TO 
  
 postgres 
 ;

    11. Create the schema that contains the tables.

        CREATE 
  
 SCHEMA 
  
 store 
 ;

    12. Create the tables and insert data.

        CREATE 
  
 TABLE 
  
 store 
 . 
 checked_items 
 ( 
 bag_id 
  
 INT 
 , 
 timestamp 
  
 TIMESTAMP 
 , 
  
 loc_code 
  
 CHAR 
 ( 
 3 
 ), 
  
 scan_type 
  
 CHAR 
 ( 
 1 
 ), 
  
 location 
  
 TEXT 
 , 
  
 customer_id 
  
 INT 
 ); 
 INSERT 
  
 INTO 
  
 store 
 . 
 checked_items 
  
 ( 
 bag_id 
 , 
  
 timestamp 
 , 
  
 loc_code 
 , 
  
 scan_type 
 , 
  
 location 
 , 
  
 customer_id 
 ) 
  
 VALUES 
 ( 
 101 
 , 
  
 '2023-10-26 10:00:00' 
 , 
  
 'ABC' 
 , 
  
 'I' 
 , 
  
 'Warehouse A' 
 , 
  
 123 
 ), 
 ( 
 102 
 , 
  
 '2023-10-26 10:15:30' 
 , 
  
 'DEF' 
 , 
  
 'O' 
 , 
  
 'Loading Dock B' 
 , 
  
 456 
 ), 
 ( 
 103 
 , 
  
 '2023-10-26 10:30:45' 
 , 
  
 'GHI' 
 , 
  
 'I' 
 , 
  
 'Conveyor Belt 1' 
 , 
  
 789 
 ), 
 ( 
 104 
 , 
  
 '2023-10-26 11:00:00' 
 , 
  
 'JKL' 
 , 
  
 'O' 
 , 
  
 'Shipping Area C' 
 , 
  
 101 
 ), 
 ( 
 105 
 , 
  
 '2023-10-26 11:45:15' 
 , 
  
 'MNO' 
 , 
  
 'I' 
 , 
  
 'Sorting Station D' 
 , 
  
 202 
 ), 
 ( 
 106 
 , 
  
 '2023-10-26 12:00:00' 
 , 
  
 'PQR' 
 , 
  
 'O' 
 , 
  
 'Truck Bay E' 
 , 
  
 303 
 );

    Create parameterized secure views and set up access privileges

    To create parameterized secure views and to set up appropriate access privileges for the base table and views, follow these steps:

    1. In the Google Cloud console, go to the Cloud SQL page.

      Go to Cloud SQL

    2. Select an instance from the list.

    3. In the navigation menu, click Cloud SQL Studio.

    4. Sign in to Studioand connect to the database as the postgres .

    5. Click Authenticate. The Explorer pane displays a list of the objects in your database.

    6. Click New SQL editor tabor New tabto open a new tab.

    7. To provide limited access to the view, create a parameterized view:

        CREATE 
  
 VIEW 
  
 store 
 . 
 secure_checked_items 
  
 WITH 
  
 ( 
 security_barrier 
 ) 
  
 AS 
 SELECT 
  
 bag_id 
 , 
  
 timestamp 
 , 
  
 location 
 FROM 
  
 store 
 . 
 checked_items 
  
 t 
 WHERE 
  
 customer_id 
  
 = 
  
 $ 
 @ 
 app_end_userid 
 ;

    8. Grant access to the view.

        GRANT 
  
 SELECT 
  
 ON 
  
 store 
 . 
 secure_checked_items 
  
 TO 
  
 psv_user 
 ;

    9. To access the view, grant access to the schema.

        GRANT 
  
 USAGE 
  
 ON 
  
 SCHEMA 
  
 store 
  
 TO 
  
 psv_user 
 ;

    10. Revoke direct access to the base table.

        REVOKE 
  
 ALL 
  
 PRIVILEGES 
  
 ON 
  
 store 
 . 
 checked_items 
  
 FROM 
  
 psv_user 
 ;

      Note:The owner of the parameterized view must have SELECT privileges on the base tables. In addition, the user of the parameterized view must have USAGE on the schema of the view and SELECT on the view. For example, the postgres user owns the parameterized view, so it has SELECT privileges on the base tables while the psv_user must have USAGE on the store schema and SELECT on the view.

    11. Sign in as the postgres administrator, and grant the psv_user role to an IAM-authenticated user:

        GRANT 
  
 psv_user 
  
 TO 
  
 " IAM_USER_EMAIL 
" 
 ;

      Replace IAM_USER_EMAIL with your IAM user email address.

    Verify data security

    To verify that the parameterized secure views are restricting access to the designated views, sign into the database as the IAM-authenticated user. In Cloud SQL, IAM users inherit the permissions of the database roles assigned to them.

    1. Sign into the database as the IAM-authenticated user.

    2. Verify that the base table can't be accessed.

        SELECT 
  
 * 
  
 FROM 
  
 store 
 . 
 checked_items 
 ; 
 ERROR 
 : 
  
 permission 
  
 denied 
  
 for 
  
 table 
  
 checked_items

    3. Access the parameterized secure views using the execute_parameterized_query function:

        SELECT 
  
 * 
  
 FROM 
  
 parameterized_views 
 . 
 execute_parameterized_query 
 ( 
  
 query 
  
 = 
>  
 'SELECT * from store.secure_checked_items' 
 , 
  
 param_names 
  
 = 
>  
 ARRAY 
  
 [ 
 'app_end_userid' 
 ], 
  
 param_values 
  
 = 
>  
 ARRAY 
  
 [ 
 '303' 
 ] 
 );

      1. Query the parameterized secure views using SQL syntax and the QueryData request with PSV parameters.

           
curl  
-X  
POST  
 \ 
  
 "https://geminidataanalytics.googleapis.com/v1beta/projects/ PROJECT_ID 
/locations/ REGION 
:queryData" 
  
 \ 
  
-H  
 "Authorization: Bearer 
 $( 
gcloud  
auth  
print-access-token ) 
 " 
  
 \ 
  
-H  
 "Content-Type: application/json; charset=utf-8" 
  
 \ 
  
-d  
 '{ 
 "prompt": "Show me the checked items.", 
 "context": { 
 "datasource_references": { 
 "cloud_sql_reference": { 
 "database_reference": { 
 "engine": "POSTGRESQL", 
 "project_id": " PROJECT_ID 
", 
 "region": " REGION 
", 
 "instance_id": " INSTANCE_ID 
", 
 "database_id": " DATABASE_ID 
" 
 } 
 } 
 }, 
 "parameterized_secure_view_parameters": { 
 "parameters": { 
 "app_end_userid": "303" 
 } 
 } 
 }, 
 "generation_options": { 
 "generate_query_result": true, 
 "generate_natural_language_answer": true, 
 "generate_explanation": true 
 } 
 }'

        Replace the following values:

        • PROJECT_ID : Your Google Cloud project ID.
        • REGION : The region where your Cloud SQL for PostgreSQL instance is located.
        • INSTANCE_ID : The ID of your Cloud SQL for PostgreSQL instance.
        • DATABASE_ID : The ID of your Cloud SQL for PostgreSQL database.

      Clean up

      Delete the cluster

      When you delete the cluster that you created in the before you begin section, you also delete all of the objects you created.

      1. In the Google Cloud console, go to the Cloud SQL page.

        Go to Cloud SQL

      2. Select an instance from the list.

      3. Click Delete.

      4. Confirm that you want to delete the instance by entering the instance name and clicking Delete.
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