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Databases of live websites often contain personally identifiable information (PII) such as full names, mailing addresses, and phone numbers. To ensure people reviewing code changes can’t access information they shouldn’t, sanitize your databases of any PII that they may contain. This example goes through the process for a MySQL database using Drupal.

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Before you begin

You need:
  • A project with a MySQL database.
  • A command interface installed:
    • If doing it manually, the Upsun CLI.
    • Otherwise, make sure Drush is installed in your environment.
This guide is about sanitizing MySQL databases. This guide doesn’t address:
  • Sanitizing NoSQL Databases (such as MongoDB)
  • Input validation and input sanitization, which both help prevent security vulnerabilities

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Sanitize the database

Make sure that you only sanitize preview environments and never the production environment. Otherwise you may lose most or even all of the relevant data stored in your database. First, take a database dump of your preview environment. This is just a safety precaution. Production data isn’t altered. To get a database dump, run the following command: upsun db:dump -e DEVELOPMENT_ENVIRONMENT_NAME.
Assumptions:
  • users is the table where all of your PII is stored in the staging development database.
  • staging is an exact copy of your production database.
  1. Connect to the staging database by running upsun sql -e staging.
  2. Display all fields from your users table, to select which ones need to be redacted. Run the following query: 
    MariaDB [main]> SELECT * FROM users;
    You see output like the following: 
    +----+------------+---------------+---------------------------+---------------+
| ID | first_name | last_name     | user_email                | display_name  |
+----+------------+---------------+---------------------------+---------------+
|  1 | admin      | admin         | admin@yourcompany.com     | admin         |
|  2 | john       | doe           | john.doe@gmail.com        | john          |
|  3 | jane       | doe           | janedoe@ymail.com         | jane          |
+----+------------+---------------+---------------------------+---------------+
  3. Change the fields where PII is contained with the UPDATE statement. For example, to change the display name of users with an email address not in your company’s domain to a random value, run the following query: 
    UPDATE users
SET display_name==substring(md5(display_name||'$PLATFORM_PROJECT_ENTROPY') for 8);
WHERE email NOT LIKE '%@yourcompany%'
    Adapt and run that query for all fields that you need to sanitize. If you modify fields that you shouldn’t alter, you can restore them from the dump you took in step 1. You can create a script to automate the sanitization process to be run automatically on each new deployment. Once you have a working script, add your script to sanitize the database to a deploy hook: 
    applications:
    myapp:

        # ...

        hooks:
            deploy: |

                # ...

                cd /app/public
                if [ "$PLATFORM_ENVIRONMENT_TYPE" = production ]; then
                    # Do whatever you want on the production site.
                else
                    # The sanitization of the database should happen here (since it's non-production)
                    sanitize_the_database.sh
                fi

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What’s next

You learned how to remove sensitive data from a database. To replace sensitive data with other meaningful data, you can add a faker to the process. A faker is a program that generates fake data that looks real. Having meaningful PII-free data allows you to keep your current Q&A, external reviews, and other processes. To add a faker, adapt your sanitizing queries to replace each value that contains PII with a new value generated by the faker. You might also want to make sure that you implement input validation. If your database contains a lot of data, consider using the OPTIMIZE TABLE statement to reduce its size and help improve performance.
Last modified on March 12, 2026