Contents

PostgreSQL Anonymizer 0.12: Release Candidate 2

Limoges, France, April 10, 2022

PostgreSQL Anonymizer is an extension that hides or replaces personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

The extension supports 3 different anonymization strategies: Dynamic Masking, Static Masking and Anonymous Dumps. It also offers a large choice of Masking Functions such as Substitution, Randomization, Faking, Pseudonymization, Partial Scrambling, Shuffling, Noise Addition and Generalization.

Towards version 1.0 and beyond !

This releases is focused on fixing remaining bugs and removing obsoletes parts of the code.

4 New Parameters !

This version introduces 4 new GUC parameters:

  • anon.maskschema
  • anon.sourceschema
  • anon.algorithm
  • anon.salt

Those values were previously stored in 2 tables anon.config and anon.secret. They both are obsolete now.

Read the "Configure" section below for more details:

https://postgresql-anonymizer.readthedocs.io/en/latest/configure/

How to Install

This extension is officially supported on PostgreSQL 9.6 and further versions.

On Red Hat, CentOS and Rocky Linux systems, you can install it directly from the official PostgreSQL RPM repository:

dnf install postgresql_anonymizer14

Then load the extension with:

ALTER DATABASE foo SET session_preload_libraries = 'anon';

Create the extension inside the database:

CREATE EXTENSION anon CASCADE;

And finally, initialize the extension

SELECT anon.init();

For other systems, check out the install documentation:

https://postgresql-anonymizer.readthedocs.io/en/latest/INSTALL/

Thanks

This release includes code, bugfixes, documentation, code reviews and ideas from Radek Salač and others we may have missed.

Many thanks to them!

How to contribute

PostgreSQL Anonymizer is part of the Dalibo Labs initiative. It is mainly developed by Damien Clochard.

This is an open project, contributions are welcome. 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.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/dalibo/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs

PostgreSQL Anonymizer 0.11: Release Candidate 1

Paris, France, March 31, 2022

PostgreSQL Anonymizer is an extension that hides or replaces personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

The extension supports 3 different anonymization strategies: Dynamic Masking, Static Masking and Anonymous Dumps. It also offers a large choice of Masking Functions such as Substitution, Randomization, Faking, Pseudonymization, Partial Scrambling, Shuffling, Noise Addition and Generalization.

Towards version 1.0 and beyond !

This releases does not introduce major changes. It is focused on fixing remaining bugs and removing obsoletes parts of the code.

In previous versions we allowed users de declare masking rules using a COMMENT statement. This is not supported anymore. Use SECURITY LABEL FOR anon to declare your rules... And use COMMENT to declare comments :)

How to Install

This extension is officially supported on PostgreSQL 9.6 and further versions.

On Red Hat, CentOS and Rocky Linux systems, you can install it directly from the official PostgreSQL RPM repository:

dnf install postgresql_anonymizer14

Then load the extension with:

ALTER DATABASE foo SET session_preload_libraries = 'anon';

Create the extension inside the database:

CREATE EXTENSION anon CASCADE;

And finally, initialize the extension

SELECT anon.init();

For other systems, check out the install documentation:

https://postgresql-anonymizer.readthedocs.io/en/latest/INSTALL/

Thanks

This release includes code, bugfixes, documentation, code reviews and ideas from Christophe Courtois, Hrvoje Pavlinovic, Mike Tefft, Cristian Gomez Portes and others we may have missed.

Many thanks to them!

How to contribute

PostgreSQL Anonymizer is part of the Dalibo Labs initiative. It is mainly developed by Damien Clochard.

This is an open project, contributions are welcome. 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.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/dalibo/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs

PostgreSQL Anonymizer 0.10: An improved engine and a brand new tutorial

Paris, France, March 14, 2022

PostgreSQL Anonymizer is an extension that hides or replaces personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

The extension supports 3 different anonymization strategies: Dynamic Masking, Static Masking and Anonymous Dumps. It also offers a large choice of Masking Functions such as Substitution, Randomization, Faking, Pseudonymization, Partial Scrambling, Shuffling, Noise Addition and Generalization.

Many improvements and a better dynamic masking engine

This version is a major step toward the upcoming version 1.0 which will be considered as production ready.

The main changes are focused on the pg_dump_anon.sh wrapper which is now faster and more accurate.

The dynamic masking engine has been simplified and improved. The change is not visible for end users but the inner workings are now more robust, in particular the main event trigger that hides the real data to the masked roles.

A brand new tutorial

Anonymization can be a difficult task and sometimes we just don't know where to start ! In addition to the [project documentation], we are now publishing a complete 4-hours workshop with practical examples, a series of exercises and their solutions.

The result is a 50 pages document designed as a kickstarter to help you discover how you can use PostgreSQL Anonymizer to protect the privacy and comply to the GDPR requirements.

The tutorial is available here:

https://dali.bo/howto_anon_handout

How to Install

This extension is officially supported on PostgreSQL 9.6 and further versions.

On Red Hat, CentOS and Rocky Linux systems, you can install it directly from the official PostgreSQL RPM repository:

dnf install postgresql_anonymizer14

Then load the extension with:

ALTER DATABASE foo SET session_preload_libraries = 'anon';

Create the extension inside the database:

CREATE EXTENSION anon CASCADE;

And finally, initialize the extension

SELECT anon.init();

For other systems, check out the install documentation:

https://postgresql-anonymizer.readthedocs.io/en/latest/INSTALL/

Thanks

This release includes code, bugfixes, documentation, code reviews and ideas from Be Hai Tran, Florent Jardin, Yann B., Christophe Courtois, Vito Botta, Cristiano S., Adrien S., Justin Wei (and others we may have missed).

Many thanks to them!

A final special thanks goes to Frédéric Yhuel for his work on the pl/pgsql code and the documentation !

How to contribute

PostgreSQL Anonymizer is part of the Dalibo Labs initiative. It is mainly developed by Damien Clochard.

This is an open project, contributions are welcome. 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.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/dalibo/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs

PostgreSQL Anonymizer 0.9: Trusted Schemas and Support for PostgreSQL 14

Paris, France, July 2nd, 2021

PostgreSQL Anonymizer is an extension that hides or replaces personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

The extension supports 3 different anonymization strategies: Dynamic Masking, Static Masking and Anonymous Dumps. It also offers a large choice of Masking Functions such as Substitution, Randomization, Faking, Pseudonymization, Partial Scrambling, Shuffling, Noise Addition and Generalization.

Reject masking filters if they don't belong to a trusted schema

With PostgreSQL Anonymizer, the database owner can define custom masking filters that would hide sensitive information based on internal business rules, for instance a specific masking function that would remove names and phone numbers from a JSON document.

For security reasons, the database administrator may want to restrict this feature by accepting only the masking filters located inside a trusted schema.

To activate this security barrier, the administrator can simply enable a GUC option called anon.restrict_to_trusted_schemas:

ALTER SYSTEM SET anon.restrict_to_trusted_schemas = on;

And then declare which schemas are trusted:

SECURITY LABEL FOR anon ON SCHEMA foo IS 'TRUSTED';

By default, the schemas pg_catalog and anon are trusted. The public schema is not trusted (and it should never be...).

IMPORTANT: Activating this parameter may break some pre-existing masking rules! If that's the case, the database administrator may have to move some custom masking functions inside a trusted schema. For now, this parameter is disabled by default. However it will be set to 'on' by default in future versions.

Users are strongly encouraged to activate this option as soon as possible.

Warning: Support for Amazon RDS is now deprecated

As announced in the previous version, we made the difficult choice to drop the so-called standalone installation method. In practice, the anon_standalone.sql file will not evolve anymore.

As a collateral effect, this means the extension won't work on most of the Postgres-as-a-Service platforms, such as Amazon RDS, unless they decide to actively support it.

If privacy and anonymity are a concern to you, we encourage you to contact the customer services of these platforms and ask them if they plan to add this extension to their catalog.

How to Install

This extension is officially supported on PostgreSQL 9.6 and further versions.

On Red Hat, CentOS and Rocky Linux systems, you can install it directly from the official PostgreSQL RPM repository:

yum install postgresql_anonymizer12

Then load the extension with:

ALTER DATABASE foo SET session_preload_libraries = 'anon';

Create the extension inside the database:

CREATE EXTENSION anon CASCADE;

And finally, initialize the extension

SELECT anon.init();

For other systems, check out the install documentation:

https://postgresql-anonymizer.readthedocs.io/en/latest/INSTALL/

WARNING: The project is still under active development and should be used carefully.

Thanks

This release includes code, bugfixes and ideas from Carlos Medeiros, Devrim Gündüz, Andreas D, Thibaut Madelaine.

Many thanks to them!

How to contribute

PostgreSQL Anonymizer is part of the Dalibo Labs initiative. It is mainly developed by Damien Clochard and Frédéric Yhuel

This is an open project, contributions are welcome. 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.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/dalibo/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs

PostgreSQL Anonymizer 0.8: Masking foreign tables and partitions

Paris, France, February 8, 2021

PostgreSQL Anonymizer is an extension that hides or replaces personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

The extension supports 3 different anonymization strategies: Dynamic Masking, Static Masking and Anonymous Dumps. It also offers a large choice of Masking Functions such as Substitution, Randomization, Faking, Pseudonymization, Partial Scrambling, Shuffling, Noise Addition and Generalization.

Improve performances and randomness

Our latest efforts were focused on performance and improving the shuffle algorithm and fake data filters. You may also notice that the anonymize_database function is much faster.

Support for foreign tables and partitions

You can now declare masking rules on partitions, inherited tables and foreign tables. However keep in mind that the masking rules are NOT INHERITED. If you have split a table into multiple partitions, you need to declare the masking rules for each partition.

Warning: Support for Amazon RDS will be deprecated in the next version

This extension was never really intended to work on Database As A Service platforms (such as Amazon RDS or Google Cloud SQL). It just happens to work currently using the standalone installation method but we will no longer actively support it. In practice, the anon_standalone.sql file will not evolve anymore.

In future versions, we will introduce features that will force us to deprecate this method. If privacy and anonymity are a concern to you, we encourage you to contact the customer services of these platforms and ask them if they plan to add this extension to their catalog.

How to Install

This extension is officially supported on PostgreSQL 9.6 and further versions.

On Red Hat / CentOS systems, you can install it from the official PostgreSQL RPM repository:

yum install postgresql_anonymizer12

Then load the extension with:

ALTER DATABASE foo SET session_preload_libraries = 'anon';

Create the extension inside the database:

CREATE EXTENSION anon CASCADE;

And finally, initialize the extension

SELECT anon.init();

For other systems, check out the install documentation :

https://postgresql-anonymizer.readthedocs.io/en/latest/INSTALL/

WARNING: The project is still under active development and should be used carefully.

Thanks

This release includes code, bugfixes and ideas from Rushal Verma, Paul Bonaud, Dmitry Fomin, Rodrigo Otsuka , Nicolas Peltier, Matthieu Larcher and others.

Many thanks to them!

How to contribute

PostgreSQL Anonymizer is part of the Dalibo Labs initiative. It is mainly developed by Damien Clochard.

This is an open project, contributions are welcome. 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.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/dalibo/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs

PostgreSQL Anonymizer 0.7: Generic Hashing and Advanced Faking

Eymoutiers, France, September 25, 2020

PostgreSQL Anonymizer is an extension that hides or replaces personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

The extension supports 3 different anonymization strategies: Dynamic Masking, In-Place Anonymization and Anonymous Dumps. It also offers a large choice of Masking Functions such as Substitution, Randomization, Faking, Pseudonymization, Partial Scrambling, Shuffling, Noise Addition and Generalization.

Generic Hashing

In theory, hashing is not a valid anonymization technique, however in practice it is sometimes necessary to generate a determinist hash of the original data. For instance, when a pair of primary key / foreign key is a "natural key", it may contain actual information (like a customer number containing a birth date or something similar).

Hashing such columns allows to keep referential integrity intact even for relatively unusual source data. Therefore, the extension provides 2 masking functions:

  • anon.hash(value) will return a text hash of the value using a secret salt and a secret hash algorithm (see below)

  • anon.digest(value,salt,algorithm) lets you choose a salt and the hash algorithm you want to use

By default a random secret salt is generated when the extension is initialized and the default hash algortihm is sha512. You can change that if needed.

Keep in mind that hashing is a form of Pseudonymization. This means that the real data can be rebuilt using the hashed value and the masking function. If an attacker gets access to these elements, he or she can easily re-identify some persons using brute force or dictionary attacks. Therefore, the salt and the algorithm used to hash the data must be protected with the same level of security that the original dataset.

Many thanks to Gunnar "Nick" Bluth for his help on this feature !

Advanced Faking

Generating fake data is a complex topic. The anon extension offers a set of basic faking functions but for more advanced faking methods, in particular if you are looking for localized fake data, take a look at PostgreSQL Faker, an extension based upon the well-known Faker python library.

This extension provides an advanced faking engine with localisation support

For example:

CREATE SCHEMA faker;
CREATE EXTENSION faker SCHEMA faker;
SELECT faker.faker('de_DE');
SELECT faker.first_name_female();
 first_name_female
-------------------
 Mirja

How to Install

This extension is officially supported on PostgreSQL 9.6 and further versions.

On Red Hat / CentOS systems, you can install it from the official PostgreSQL RPM repository:

yum install postgresql_anonymizer12

Then load the extension with:

ALTER DATABASE foo SET session_preload_libraries = 'anon';

Create the extension inside the database:

CREATE EXTENSION anon CASCADE;

And finally, initialize the extension

SELECT anon.init();

For other systems, check out the install documentation :

https://postgresql-anonymizer.readthedocs.io/en/latest/INSTALL/

WARNING: The project is at an early stage of development and should be used carefully.

Thanks

This release includes code, bugfixes and ideas from Gunnar "Nick" Bluth, Yann Robin, Christophe Courtois, Nikolay Samokhvalov.

Many thanks to them !

How to contribute

PostgreSQL Anonymizer is part of the Dalibo Labs initiative. It is mainly developed by Damien Clochard.

This is an open project, contributions are welcome. 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.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/dalibo/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs

PostgreSQL Anonymizer 0.6: Pseudonymization and Improved Anonymous Exports

Eymoutiers, France, Mars 5, 2020

PostgreSQL Anonymizer is an extension that hides or replaces personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

The extension supports 3 different anonymization strategies: Dynamic Masking, In-Place Anonymization and Anonymous Dumps. It also offers a large choice of Masking Functions: Substitution, Randomization, Faking, Pseudonymization, Partial Scrambling, Shuffling, Noise Addition and Generalization.

Pseudonymization

Pseudonymization functions are similar to the faking functions in the sense that they generate realistic values. The main difference is that pseudonymization is deterministic : the functions will always return the same fake value based on a seed and an optional salt.

# SELECT anon.pseudo_email('Alice','salt123');
   pseudo_email
-------------------
 fcadell56@ucoz.ru
# SELECT anon.pseudo_email('Alice','salt123');
   pseudo_email
-------------------
 fcadell56@ucoz.ru

WARNING : Pseudonymization is often confused with anonymization but in fact they serve 2 different purposes. With pseudonymization, the real data can be rebuilt using the pseudo data and the masking rule. If an attacker gets access to these elements, he or she can easily re-identify some people using brute force or dictionary attacks. Therefore, you should protect any pseudonymized data with the same level of security that the original dataset. The GDPR makes it very clear that personal data which have undergone pseudonymization are still considered to be personal information.

Improved Anonymous Exports

The anon.dump() function was slow and unpractical. It is now deprecated and replace by a tool named pg_dump_anon that you can use like the regular pg_dump command:

pg_dump_anon -h localhost -U bob mydb > anonymous_dump.sql

It uses the same connections parameters that pg_dump. The PostgreSQL environment variables ($PGHOST, PGUSER, etc.) and .pgpass are supported. However the plain format is the only supported format. The other formats (custom, dir and tar) are not supported.

Detecting Hidden Identifiers

This extension makes it very easy to declare masking rules. But of course when you're creating an anonymization strategy, the hard part is to scan the database model to find which columns contains direct and indirect identifiers and then decide how these identifiers should be masked.

We now provide a detect() function that will search for common identifiers names based on a dictionary. For now, 2 dictionaries are available: English ('en_US') and French ('fr_FR'). By default the English dictionary is used:

# SELECT anon.detect('en_US');
 table_name |  column_name   | identifiers_category | direct
------------+----------------+----------------------+--------
 customer   | CreditCard     | creditcard           | t
 customer   | id             | account_id           | t
 vendor     | Firstname      | firstname            | t

The identifier categories are based on the HIPAA classification.

How to Install

This extension is officially supported on PostgreSQL 9.6 and later.

On Red Hat / CentOS systems, you can install it from the official PostgreSQL RPM repository:

yum install postgresql_anonymizer12

Then add 'anon' in the shared_preload_libraries parameter of your postgresql.conf file. And restart your instance.

For other systems, check out the install documentation :

https://postgresql-anonymizer.readthedocs.io/en/latest/INSTALL/

WARNING: The project is at an early stage of development and should be used carefully.

Thanks

This release includes code, bugfixes and ideas from Sebastien Delobel, Sam Buckingham, Thomas Clark, Joe Auty, Pierre-Henri Dubois Amy and Olleg Samoylov.

Many thanks to them !

How to contribute

PostgreSQL Anonymizer is part of the Dalibo Labs initiative. It is mainly developed by Damien Clochard.

This is an open project, contributions are welcome. 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.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/dalibo/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs

PostgreSQL Anonymizer 0.5: Generalization and k-anonymity

Eymoutiers, France, November 6, 2019

Postgresql Anonymizer is an extension that hides or replaces personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

The extension supports 3 different anonymization strategies: Dynamic Masking, In-Place Anonymization and Anonymous Dumps. It also offers a large choice of Masking Functions: Substitution, Randomization, Faking, Partial Scrambling, Shuffling, Noise Addition and Generalization.

Generalization

The idea of generalization is to replace data with a broader, less accurate value. For instance, instead of saying "Bob is 28 years old", you can say "Bob is between 20 and 30 years old". This is interesting for analytics because the data remains true while avoiding the risk of re-identification.

PostgreSQL can handle generalization very easily with the RANGE data types, a very poweful way to store and manipulate a set of values contained between a lower and an upper bound.

Here's a basic table containing medical data:

SELECT * FROM patient;
     ssn     | firstname | zipcode |   birth    |    disease
-------------+-----------+---------+------------+---------------
 253-51-6170 | Alice     |   47012 | 1989-12-29 | Heart Disease
 091-20-0543 | Bob       |   42678 | 1979-03-22 | Allergy
 565-94-1926 | Caroline  |   42678 | 1971-07-22 | Heart Disease
 510-56-7882 | Eleanor   |   47909 | 1989-12-15 | Acne

We want the anonymized data to remain true because it will be used for statistics. We can build a view upon this table to remove useless columns and generalize the indirect identifiers (zipcode and birthday):

CREATE MATERIALIZED VIEW generalized_patient AS
SELECT
  'REDACTED'::TEXT AS firstname,
  anon.generalize_int4range(zipcode,1000) AS zipcode,
  anon.generalize_daterange(birth,'decade') AS birth,
  disease
FROM patient;

This will give us a less accurate view of the data:

SELECT * FROM generalized_patient;
 firstname |    zipcode    |          birth          |    disease
-----------+---------------+-------------------------+---------------
 REDACTED  | [47000,48000) | [1980-01-01,1990-01-01) | Heart Disease
 REDACTED  | [42000,43000) | [1970-01-01,1980-01-01) | Allergy
 REDACTED  | [42000,43000) | [1970-01-01,1980-01-01) | Heart Disease
 REDACTED  | [47000,48000) | [1980-01-01,1990-01-01) | Acne

k-anonymity

k-anonymity is an industry-standard term used to describe a property of an anonymized dataset. The k-anonymity principle states that within a given dataset, any anonymized individual cannot be distinguished from at least k-1 other individuals. In other words, k-anonymity might be described as a "hiding in the crowd" guarantee. A low value of k indicates there's a risk of re-identification using linkage with other data sources.

You can evaluate the k-anonymity factor of a table in 2 steps :

Step 1: First defined the columns that are [indirect idenfiers] ( also known as "quasi identifers") like this:

SECURITY LABEL FOR anon ON COLUMN generalized_patient.zipcode
IS 'INDIRECT IDENTIFIER';

SECURITY LABEL FOR anon ON COLUMN generalized_patient.birth
IS 'INDIRECT IDENTIFIER';

Step 2: Once the indirect identifiers are declared :

SELECT anon.k_anonymity('generalized_patient')

In the example above, the k-anonymity factor of the generalized_patient materialized view is 2.

Lorem Ipsum

For TEXT and VARCHAR columns, you can now use the classic Lorem Ipsum generator:

  • anon.lorem_ipsum() returns 5 paragraphs
  • anon.lorem_ipsum(2) returns 2 paragraphs
  • anon.lorem_ipsum( paragraphs := 4 ) returns 4 paragraphs
  • anon.lorem_ipsum( words := 20 ) returns 20 words
  • anon.lorem_ipsum( characters := 7 ) returns 7 characters

How to Install

This extension is officially supported on PostgreSQL 9.6 and later.

On Red Hat / CentOS systems, you can install it from the official PostgreSQL RPM repository:

yum install postgresql_anonymizer12

Then add 'anon' in the shared_preload_libraries parameter of your postgresql.conf file. And restart your instance.

For other system, check out the install documentation :

https://postgresql-anonymizer.readthedocs.io/en/latest/INSTALL/

WARNING: The project is at an early stage of development and should be used carefully.

Thanks

This release includes code and ideas from Travis Miller, Jan Birk and Olleg Samoylov. Many thanks to them !

How to contribute

PostgreSQL Anonymizer is part of the Dalibo Labs initiative. It is mainly developed by Damien Clochard.

This is an open project, contributions are welcome. 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.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/dalibo/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs

PostgreSQL Anonymizer 0.4 : Declare Masking Rules With Security Labels

Eymoutiers, October 14, 2019

Postgresql Anonymizer is an extension that hides or replaces personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

This new version introduces a major change of syntax. In the previous versions, the data masking rules were declared with column comments. They are now defined by using security labels:

SECURITY LABEL FOR anon
ON COLUMN customer.lastname
IS 'MASKED WITH FUNCTION anon.fake_last_name()'

The previous syntax is still supported and backward compatibility is maintained.

How to Install

This extension is officially supported on PostgreSQL 9.6 and later.

It requires extension named tsm_system_rows (available in the contrib package) and an extension called ddlx (available via PGXN) :

pgxn install ddlx
pgxn install postgresql_anonymizer

Then add 'anon' in the shared_preload_libraries parameter of your postgresql.conf file. And restart your instance.

WARNING: The project is at an early stage of development and should be used carefully.

How to contribute

PostgreSQL Anonymizer is part of the Dalibo Labs initiative. It is mainly developed by Damien Clochard.

This is an open project, contributions are welcome. 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.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/dalibo/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs

PostgreSQL Anonymizer 0.3 : In-Place Masking and Anonymous Dumps

Paris, August 26, 2019

postgresql_anonymizer is an extension that hides or replaces personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

Firts of all, you declare a list of Masking Rules directly inside the database model with SQL comments like this :

COMMENT ON COLUMN users.name IS 'MASKED WITH FUNCTION md5(name)';

Once the masking rules are declared, anonymization can be acheived in 3 different ways:

In addition, various Masking Functions are available : randomization, faking, partial scrambling, shuffling, noise, etc... You can also user your own custom function !

For more detail, please take a look at the documention: https://postgresql-anonymizer.readthedocs.io/

How to Install

This extension is officially supported on PostgreSQL 9.6 and later.

It requires extension named tsm_system_rows (available in the contrib package) and an extension called ddlx (available via PGXN) :

pgxn install ddlx
pgxn install postgresql_anonymizer

WARNING: The project is at an early stage of development and should be used carefully.

How to contribute

PostgreSQL Anonymizer is part of the Dalibo Labs initiative. It is mainly developed by Damien Clochard.

This is an open project, contributions are welcome. 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.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/dalibo/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs

Introducing PostgreSQL Anonymizer 0.2.1 !

Paris, october 29, 2018

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

The projet is aiming toward a declarative approach of anonymization. This means we're trying to extend PostgreSQL's Data Definition Language (DDL) in order to specify the anonymization strategy inside the table definition itself.

The extension can be used to put dynamic masks on certain users or permanently modify sensitive data. Various masking techniques are available : randomization, partial scrambling, custom rules, etc.

This tool is distributed under the PostgreSQL licence and the code is here:

https://gitlab.com/daamien/postgresql_anonymizer

Example

Imagine a people table

=# SELECT * FROM people;
  id  |      name      |   phone
------+----------------+------------
 T800 | Schwarzenegger | 0609110911

STEP 1 : Activate the masking engine

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

STEP 2 : Declare a masked user

=# CREATE ROLE skynet;
=# COMMENT ON ROLE skynet IS 'MASKED';

STEP 3 : Declare the masking rules

=# COMMENT ON COLUMN people.name
-# IS 'MASKED WITH FUNCTION anon.random_last_name()';

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

STEP 4 : Connect with the masked user

=# \! psql test -U skynet -c 'SELECT * FROM people;'
  id  |   name   |   phone
------+----------+------------
 T800 | Nunziata | 06******11

How to Install

This extension is officially supported on PostgreSQL 9.6 and later. It should also work on PostgreSQL 9.5 with a bit of hacking.

It requires an extension named tsm_system_rows, which is delivered by the postgresql-contrib package of the main linux distributions

You can install it with pgxn or build from source it like any other extenstion.

WARNING: The project is at an early stage of development and should be used carefully.

How to contribute

I'd like to thanks all my wonderful colleagues at Dalibo for their support and especially Thibaut Madelaine for the initial ideas.

This is an open project, contributions are welcome. I need your feedback and ideas ! Let me know what you think of this tool, how it fits your needs and what features are missing.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/daamien/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs