SQL Server is a powerful relational database management system that offers various security features to protect sensitive data. One such feature is row-level security, introduced in SQL Server 2016. Row-level security allows you to control access to individual rows of data, providing fine-grained control over who can view, modify, or delete specific data.

Prior to row-level security, SQL Server granted access at the table or view level, making it challenging to restrict access to specific rows. With row-level security, you can define predicates, which are SQL functions that determine whether a user has access to a particular row. These predicates are automatically invoked when accessing a table, ensuring that only authorized users can view or modify the data.

Let’s consider an example to understand how row-level security works. Suppose we have a table called “Customers” with columns like “id”, “name”, and “country”. We want to restrict access to certain rows based on the user’s country and role.

To implement row-level security, we can define filter predicates and block predicates. Filter predicates are used for select, update, and delete operations, while block predicates are used for insert, update, and delete operations.

For instance, we can create a filter predicate that allows users whose names start with “EU_” to access customers in Denmark, Belgium, or Spain. Similarly, users whose names start with “NA_” can access customers in the US or Canada. We can also ensure that the “sa” user has access to all customers.

CREATE FUNCTION RestrictCustomers(@country AS sysname)
RETURNS TABLE WITH SCHEMABINDING
AS
RETURN SELECT 1 AS res
WHERE
(@country IN ('DK', 'BE', 'ES') AND USER_NAME() LIKE 'EU_%') OR
(@country IN ('US', 'CA') AND USER_NAME() LIKE 'NA_%') OR
(SUSER_NAME() = 'sa');

CREATE SECURITY POLICY CustomersPolicy
ADD FILTER PREDICATE RestrictCustomers(country)
ON Customers
WITH (STATE = ON);

In the above example, we define a function called “RestrictCustomers” that takes the country as a parameter. The function returns a table with a single column “res” that contains the value 1 if the user is allowed access to the row. We then register this function as a filter predicate using the “CREATE SECURITY POLICY” statement.

Once the row-level security is implemented, only users who meet the specified criteria will be able to access the corresponding rows. For example, if we execute a query as the user “EU_jdoe”, we will only see the customers in Denmark, Belgium, or Spain.

EXECUTE AS USER = 'EU_jdoe';
SELECT * FROM Customers;
REVERT;

While row-level security provides a level of control over data access, it’s important to note that it is not foolproof. Clever attackers can still find ways to bypass the security measures, such as using crafted SQL queries to infer the existence of restricted rows.

Alternatively, you can consider using third-party tools like Gallium Data, which offers a different approach to row-level security. Gallium Data acts as a proxy between database clients and servers, allowing you to modify SQL commands or filter result sets based on user-defined logic. This provides more flexibility in controlling data access and manipulation.

With Gallium Data, you can modify SQL commands on their way to the database server or filter the result sets coming back from the server. This allows you to hide, modify, or add rows in the result sets based on specific conditions. Gallium Data can be a valuable tool in environments where you have control over the SQL commands being executed.

It’s important to weigh the advantages and disadvantages of both SQL Server’s built-in row-level security and third-party solutions like Gallium Data. SQL Server’s row-level security is built-in, easy to implement, and performs well for simple access control scenarios. However, it may not be sufficient to protect against determined attackers.

Gallium Data, on the other hand, offers more flexibility and control over data access and manipulation. It allows you to modify SQL commands and result sets, making it suitable for complex access control requirements. However, it requires an additional system to be maintained and may introduce some performance overhead.

In conclusion, row-level security in SQL Server provides a useful mechanism for controlling access to individual rows of data. It can be a valuable tool when used in conjunction with other security measures and application logic. However, it’s important to understand its limitations and consider alternative solutions like Gallium Data for more advanced access control requirements.