在端到端工作流程中实施 pg_columnmask

本节使用一个包含敏感数据的示例员工表，完整演示了 pg_columnmask 的实施过程。您将了解如何创建自定义掩蔽函数，为各种角色（实习生、支持人员、分析师）定义具有不同权重级别的多个掩蔽策略，并观察具有单个或多个角色成员资格的用户如何查看不同级别的掩蔽数据。这些示例还涵盖了带有 RETURNING 子句的 DML 语句中的掩蔽行为、表与视图上的触发器，以及包括重命名、更改权重和清理在内的策略管理操作。

创建包含一些敏感数据的示例表：


CREATE SCHEMA hr;

CREATE TABLE hr.employees (
    id INT PRIMARY KEY,
    name TEXT NOT NULL,
    email TEXT,
    ssn TEXT,
    salary NUMERIC(10,2)
 );

INSERT INTO hr.employees VALUES
    (1, 'John Doe', 'john.doe@example.com', '123-45-6789', 50000.00),
    (2, 'Jane Smith', 'jane.smith@example.com', '987-65-4321', 60000.00);

创建自定义掩蔽函数：


CREATE OR REPLACE FUNCTION public.mask_ssn(ssn TEXT)
    RETURNS TEXT AS $$
    BEGIN
        RETURN 'XXX-XX-' || RIGHT(ssn, 4);
    END;
    $$ LANGUAGE plpgsql;

CREATE OR REPLACE FUNCTION public.mask_salary(salary NUMERIC, multiplier NUMERIC DEFAULT 0.0)
    RETURNS NUMERIC AS $$
    BEGIN
        RETURN salary * multiplier;
    END;
    $$ LANGUAGE plpgsql;

根据用户角色创建多个具有不同掩蔽级别的策略：


-- Create different roles
CREATE ROLE analyst_role;
CREATE ROLE support_role;
CREATE ROLE intern_role;

GRANT USAGE ON SCHEMA hr TO analyst_role, support_role, intern_role;
GRANT SELECT ON hr.employees TO analyst_role, support_role, intern_role;
----------------------------------------------------------------------

-- Low-Weight Policy (Intern)
CALL pgcolumnmask.create_masking_policy(
    'employee_mask_strict',
    'hr.employees',
    JSON_BUILD_OBJECT('name', 'pgcolumnmask.mask_text(name, ''*'')',
                      'email', 'pgcolumnmask.mask_email(email)',
                      'ssn', 'pgcolumnmask.mask_text(ssn, ''*'')',
                      'salary', 'public.mask_salary(salary)')::JSONB,
    ARRAY['intern_role'],
    10  -- Lowest weight
);

----------------------------------------------------------------------
-- Medium-Weight Policy (Support)
CALL pgcolumnmask.create_masking_policy(
    'employee_mask_moderate',
    'hr.employees',
    JSON_BUILD_OBJECT('email', 'pgcolumnmask.mask_email(email, ''#'')',
                      'ssn', 'public.mask_ssn(ssn)',
                      'salary', 'public.mask_salary(salary)')::JSONB,
    ARRAY['support_role'],
    50   -- Medium weight
);

----------------------------------------------------------------------
-- High-Weight Policy (Analyst)
CALL pgcolumnmask.create_masking_policy(
    'employee_mask_light',
    'hr.employees',
    JSON_BUILD_OBJECT('ssn', 'public.mask_ssn(ssn)',
                      'salary', 'public.mask_salary(salary, 0.9)')::JSONB,
    ARRAY['analyst_role'],
    100   -- Highest weight
);

以下示例演示了不同的用户如何根据其角色成员资格和策略权重来查看数据。


-- Create users
CREATE USER sarah_intern;
GRANT intern_role TO sarah_intern;

CREATE USER lisa_support;
GRANT support_role TO lisa_support;

CREATE USER mike_analyst;
GRANT analyst_role TO mike_analyst;

CREATE USER ethan_support_intern;
GRANT support_role, intern_role TO ethan_support_intern;

CREATE USER john_analyst_intern;
GRANT analyst_role, intern_role TO john_analyst_intern;

作为实习生（最严格的掩蔽）：


SET ROLE sarah_intern;

SELECT * FROM hr.employees;
 id |    name    |         email          |     ssn     | salary 
----+------------+------------------------+-------------+--------
  1 | ********   | XXXXXXXX@XXXXXXX.com   | *********** |   0.00
  2 | ********** | XXXXXXXXXX@XXXXXXX.com | *********** |   0.00

作为支持用户（中等掩蔽）：


SET ROLE lisa_support;

SELECT * FROM hr.employees;
 id |    name    |         email          |     ssn     | salary 
----+------------+------------------------+-------------+--------
  1 | John Doe   | ########@#######.com   | XXX-XX-6789 |   0.00
  2 | Jane Smith | ##########@#######.com | XXX-XX-4321 |   0.00

作为分析师（最轻的掩蔽）：


SET ROLE mike_analyst;

SELECT * FROM hr.employees;
 id |    name    |         email          |     ssn     |  salary  
----+------------+------------------------+-------------+----------
  1 | John Doe   | john.doe@example.com   | XXX-XX-6789 | 45000.00
  2 | Jane Smith | jane.smith@example.com | XXX-XX-4321 | 54000.00

作为 ethan_support_intern 用户，既是实习生，又是支持用户：


SET ROLE ethan_support_intern;

-- masking policies appliable to this user: employee_mask_strict and employee_mask_moderate
-- id : unmasked because no masking policy appliable on ethan_support_intern
--            masks these columns
-- name : masked because of employee_mask_strict policy
-- email, ssn, salary : both employee_mask_strict and employee_mask_moderate mask these columns
--                      but employee_mask_moderate will be use because of higher weight 

SELECT * FROM hr.employees;
 id |    name    |         email          |     ssn     | salary 
----+------------+------------------------+-------------+--------
  1 | ********   | ########@#######.com   | XXX-XX-6789 |   0.00
  2 | ********** | ##########@#######.com | XXX-XX-4321 |   0.00

作为 john_analyst_intern，既是实习生，又是分析师：


SET ROLE john_analyst_intern;

-- masking policies appliable to this user: employee_mask_strict and employee_mask_light
-- id : unmasked because no masking policy appliable on john_analyst_intern
--            masks these columns
-- name, email : masked because of employee_mask_strict
-- ssn, salary : both employee_mask_strict and employee_mask_light mask these columns
--               but employee_mask_light will be use because of higher weight 

SELECT * FROM hr.employees;
 id |    name    |         email          |     ssn     |  salary  
----+------------+------------------------+-------------+----------
  1 | ********   | XXXXXXXX@XXXXXXX.com   | XXX-XX-6789 | 45000.00
  2 | ********** | XXXXXXXXXX@XXXXXXX.com | XXX-XX-4321 | 54000.00

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数据掩蔽函数

DML 中的掩蔽