Contents

• Anonymization & Data Masking for PostgreSQL
  • Declaring The Masking Rules
  • Static Masking
  • Dynamic Masking
  • Anonymous Dumps
  • Support
  • Requirements
  • Install
  • Limitations
  • Performance

Anonymization & Data Masking for PostgreSQL

postgresql_anonymizer is an extension to mask or replace personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

The project relies on a declarative approach of anonymization. This means we’re using the PostgreSQL Data Definition Language (DDL) in order to specify the anonymization strategy inside the table definition itself.

Once the masking rules are defined, you can access the anonymized data in different ways :

• Anonymous Dumps : Simply export the masked data into an SQL file
• Static Masking : Remove permanently the PII according to the rules
• Dynamic Masking : Hide PII only for the masked users
• Generalization : Reducing the accuracy of dates and numbers

In addition, various Masking Functions are available: randomization, faking, partial scrambling, shuffling, noise, or even your own custom function!

Read the Concepts section for more details and NEWS.md for information about the latest version.

Declaring The Masking Rules

The main idea of this extension is to offer anonymization by design.

The data masking rules should be written by the people who develop the application because they have the best knowledge of how the data model works. Therefore masking rules must be implemented directly inside the database schema.

This allows masking the data directly inside the PostgreSQL instance without using an external tool and thus limiting the exposure and the risks of data leak.

The data masking rules are declared simply by using security labels :

=# CREATE EXTENSION IF NOT EXISTS anon CASCADE;

=# SELECT anon.init();

=# CREATE TABLE player( id SERIAL, name TEXT, points INT);

=# SECURITY LABEL FOR anon ON COLUMN player.name
-# IS 'MASKED WITH FUNCTION anon.fake_last_name()';

=# SECURITY LABEL FOR anon ON COLUMN player.id
-# IS 'MASKED WITH VALUE NULL';

Static Masking

You can permanently remove the PII from a database with anon.anonymize_database(). This will destroy the original data. Use with care.

=# SELECT * FROM customer;
 id  |   full_name      |   birth    |    employer   | zipcode | fk_shop
-----+------------------+------------+---------------+---------+---------
 911 | Chuck Norris     | 1940-03-10 | Texas Rangers | 75001   | 12
 112 | David Hasselhoff | 1952-07-17 | Baywatch      | 90001   | 423

=# SECURITY LABEL FOR anon ON COLUMN customer.full_name
-# IS 'MASKED WITH FUNCTION anon.fake_first_name() || '' '' || anon.fake_last_name()';

=# SECURITY LABEL FOR anon ON COLUMN customer.birth
-# IS 'MASKED WITH FUNCTION anon.random_date_between(''1920-01-01''::DATE,now())';

=# SECURITY LABEL FOR anon ON COLUMN customer.employer
-# IS 'MASKED WITH FUNCTION anon.fake_company()';

=# SECURITY LABEL FOR anon ON COLUMN customer.zipcode
-# IS 'MASKED WITH FUNCTION anon.random_zip()';

=# SELECT anon.anonymize_database();

=# SELECT * FROM customer;
 id  |     full_name     |   birth    |     employer     | zipcode | fk_shop
-----+-------------------+------------+------------------+---------+---------
 911 | michel Duffus     | 1970-03-24 | Body Expressions | 63824   | 12
 112 | andromach Tulip   | 1921-03-24 | Dot Darcy        | 38199   | 423

You can also use anonymize_table() and anonymize_column() to remove data from a subset of the database.

Dynamic Masking

You can hide the PII from a role by declaring it as a “MASKED”. Other roles will still access the original data.

Example:

=# SELECT * FROM people;
 id | firstname | lastname |   phone
----+----------+----------+------------
 T1 | Sarah    | Conor    | 0609110911
(1 row)

Step 1 : Activate the dynamic masking engine

=# CREATE EXTENSION IF NOT EXISTS anon CASCADE;
=# SELECT anon.start_dynamic_masking();

Step 2 : Declare a masked user

=# CREATE ROLE skynet LOGIN;
=# SECURITY LABEL FOR anon ON ROLE skynet IS 'MASKED';

Step 3 : Declare the masking rules

=# SECURITY LABEL FOR anon ON COLUMN people.lastname
-# IS 'MASKED WITH FUNCTION anon.fake_last_name()';

=# SECURITY LABEL FOR anon ON COLUMN people.phone
-# IS 'MASKED WITH FUNCTION anon.partial(phone,2,$$******$$,2)';

Step 4 : Connect with the masked user

=# \! psql peopledb -U skynet -c 'SELECT * FROM people;'
 id | firstname | lastname  |   phone
----+----------+-----------+------------
 T1 | Sarah    | Stranahan | 06******11
(1 row)

Anonymous Dumps

Due to the core design of this extension, you cannot use pg_dump with a masked user. If you want to export the entire database with the anonymized data, you must use the pg_dump_anon command line. For example

pg_dump_anon.sh -h localhost -p 5432 -U bob bob_db > dump.sql

For more details, read the Anonymous Dumps section.

Support

We need your feedback and ideas! Let us know what you think of this tool, how it fits your needs and what features are missing.

You can either open an issue or send a message at contact@dalibo.com.

Requirements

This extension works with all supported versions of PostgreSQL.

It requires an extension called pgcrypto which is delivered by the postgresql-contrib package of the main linux distributions.

Install

See the INSTALL section

Limitations

• The dynamic masking system only works with one schema (by default public). When you start the masking engine with start_dynamic_masking(), you can specify the schema that will be masked with. However static masking with anon.anonymize()and Anonymous Dumps will work fine with multiple schemas.

• The Anonymous Dumps may not be consistent. Use Static Masking combined with pg_dump if you can’t fence off your database from DML or DDL commands during the export.

Performance

See docs/performances.md