Implementing Advanced Row-Level Security in SQL Server

Row-Level Security (RLS) allows you to control which rows users can access in a database table. This is achieved by defining a security policy that applies one or more predicates to the table. These predicates are functions that filter rows based on the current user's context.

What is Row-Level Security?

RLS enhances data security by ensuring that users can only see the data they are authorized to access. It works by adding a security predicate to the query that is executed. This predicate acts as a filter, effectively restricting the rows returned by the query without requiring modifications to the application code.

Key Concepts

  • Security Predicate: A function that returns a boolean value indicating whether a row should be visible or modifiable.
  • Security Policy: A database object that binds one or more security predicates to a table or view.
  • Function: Typically, a scalar-valued function is used as a security predicate.

Creating a Security Predicate Function

A common approach is to use a function that checks a user's identity or role against a column in the table.

CREATE FUNCTION dbo.fn_RLS_TenantAccess (@TenantId INT)
RETURNS TABLE
AS
RETURN
(
    SELECT 1 AS AccessResult
    WHERE @TenantId = CAST(SESSION_CONTEXT(N'TenantId') AS INT)
);

Creating a Security Policy

Once the predicate function is created, you can associate it with a table using a security policy.

CREATE SECURITY POLICY TenantPolicy
WITH (STATE = ON)
ADD FILTER PREDICATE dbo.fn_RLS_TenantAccess(TenantId) ON dbo.YourDataTable;

Enabling and Disabling Policies

Security policies can be enabled or disabled as needed.

-- Enable
ALTER SECURITY POLICY TenantPolicy WITH (STATE = ON);

-- Disable
ALTER SECURITY POLICY TenantPolicy WITH (STATE = OFF);

Advanced Scenarios

Multi-Tenancy

RLS is highly effective for multi-tenant applications, ensuring that each tenant only accesses their own data. This is typically managed by setting a `TenantId` in the session context.

Fine-Grained Access Control

Beyond tenant isolation, RLS can be used for more granular permissions, such as limiting access to records based on department, project, or user role.

Performance Considerations

While powerful, RLS can impact query performance. It's crucial to:

  • Ensure predicate functions are efficient.
  • Utilize appropriate indexes on columns used in predicates.
  • Test performance under realistic loads.

Best Practices

  • Keep predicate functions simple and performant.
  • Use `SESSION_CONTEXT` for user-specific information.
  • Test your RLS implementation thoroughly with different user roles.
  • Document your security policies clearly.