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Author a Masking Data Policy

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Best practice: use global policies

Build global policies with tags instead of writing local policies to manage data access. This practice will prevent you from having to author or update individual policies for every data source added to Immuta.

  1. Determine your policy scope:

    • Global policy: Click the Policies icon in the navigation menu and select the Data Policies tab. Click New data policy and complete the Policy name field.

    • Local policy: Navigate to a specific data source and click the Policies tab. Scroll to the Data Policies section and click New Policy.

  2. Select Mask from the first dropdown menu.

  3. Select columns tagged, columns with any tag, columns with no tags, all columns, or columns with names spelled like.

  4. Select a masking type (some of these types will ):

  5. Select everyone except, everyone, or everyone who to continue the condition.

    • everyone except: In the subsequent dropdown menus, choose is a member of group, possesses attribute, or is acting under purpose. Complete the condition with the subsequent dropdown menus. For a list of exceptions and an explanation of their behavior, see the .

  6. Opt to complete the Enter Rationale for Policy (Optional) field, and then click Add.

  7. For global policies: Click the dropdown menu beneath Where should this policy be applied and select When selected by data owners, On all data sources, or On data sources. If you selected On data sources, finish the condition in one of the following ways:

    • tagged: Select this option and then search for tags in the subsequent dropdown menu.

    • with columns tagged

  8. Click Create Policy. If creating a global policy, you then need to click Activate Policy or Stage Policy.

  • : Enter a constant in the field that appears next to the masking type dropdown.

  • :

    1. Enter a regular expression and replacement value in the fields that appear next to the masking type dropdown.

    2. From the next dropdown, choose to make the regex Case Insensitive and/or Global. For this policy to be enforced on Redshift data sources, Global must be selected.

  • : Select the Bucket Type and then enter the bucket size.

  • : Enter the custom function native to the underlying database.

    Note: The function must be valid for the data type of the column. If it is not, the default masking type will be applied to the column.

  • for everyone who
    : Complete the
    Otherwise
    clause. You can add more than one condition by selecting
    + Add Another Condition
    . The dropdown menu in the policy builder contains conjunctions for your policy. If you select
    or
    , only one of your conditions must apply to a user for them to see the data. If you select
    and
    , all of the conditions must apply.
    : Select this option and then search for
    tags
    in the subsequent dropdown menu.
  • with column names spelled like: Select this option, and then enter a regex and choose a modifier in the subsequent fields.

  • in server: Select this option and then choose a server from the subsequent dropdown menu to apply the policy to data sources that share this connection string.

  • created between: Select this option and then choose a start date and an end date in the subsequent dropdown menus.

  • only be available for Snowflake integrations
    using hashing
    with reversibility
    Masking policies reference guide
    by making null
    using a constant
    using a regex
    by rounding
    with format preserving masking
    using randomized response
    using the custom function