Strategies to Block Access for a Specific User to a Table in BigQuery

[rafanizio92]

I'm facing challenges in attempting to block access for a specific user or
serviceAccount , to a table in Google BigQuery.

So far, I've tried several strategies, including using row-level access policies, revoking permissions, and granting permissions only to permitted users. However, I haven't been able to achieve the desired result.

Here are the strategies I've attempted:

Use of Row-Level Access Policies: I tried creating row-level access policies to deny the user's access, but faced limitations.

Revoking Permissions: I attempted to use the REVOKE command to revoke permissions but encountered issues.

Granting Permissions to Permitted Users: I tried granting permissions only to permitted users and revoking public permissions.

I would like to know if anyone in the Google Cloud community has any guidance or suggestions for successfully blocking access for the specific user and ensuring that only permitted users have access to the table.

Any help, suggestions, or guidance will be greatly appreciated. Thank you!

[ms4446]

Restricting access for a specific user or service account to a specific table in Google BigQuery requires a careful approach due to the platform's IAM-based access control mechanisms. Here's a revised breakdown of the challenges and solutions for each approach:

1. Row-Level Access Policies (RLAP):

   • RLAPs are designed for granular control over SELECT query results at the row level. They are not used to restrict access to tables or to control INSERT, UPDATE, or DELETE operations, which are managed by IAM permissions.
   • Managing RLAPs can be complex, but they are effective for fine-grained access control when configured properly.

2. Revoking Permissions:

   • To restrict access, you should ensure that the user or service account is not assigned any IAM roles at the project or dataset level that grant access to BigQuery resources.
   • Since BigQuery does not support a REVOKE command, you must remove the user or service account from the role that grants them access.

3. Granting Permissions to Permitted Users:

   • Granting permissions to specific users is a proactive approach to access control. It should be managed with a clear strategy and, where possible, automated to minimize errors.
   • This approach requires diligence to ensure that only authorized users are granted access and that permissions are kept up-to-date.

Recommendations for Effective Access Restriction:

• Utilize IAM Roles at the Dataset Level: Assign IAM roles at the dataset level to control access to all contained tables. BigQuery does not support direct table-level permissions.

• Leverage View Restrictions: Use views or authorized views to provide access to specific data within tables. This method allows you to restrict access to the underlying data while still providing necessary insights.

• Implement Custom IAM Roles: Create custom IAM roles if the predefined roles do not match your specific access requirements. Custom roles allow for precise access control tailored to your needs.

• Automate Permission Management: Employ automation tools or scripts for managing IAM roles and permissions to reduce human error and streamline the access management process.

• Regularly Review Access Policies: Conduct periodic audits of your access policies to ensure they are up-to-date with current security practices and user requirements, thus preventing unauthorized access due to outdated policies.

By following these revised recommendations, you can more effectively manage access to BigQuery tables and ensure that only authorized users and service accounts have the necessary access.