v0.2.0b1

[wwoytenko]

Greenmask 0.2.0b1

This major beta release introduces new features and refactored transformers, significantly enhancing Greenmask's flexibility to better meet business needs.

Changes overview

• Introduced dynamic parameters in the transformers

  • Most transformers now support dynamic parameters where applicable.
  • Dynamic parameters are strictly enforced. If you need to cast values to another type, Greenmask provides templates and predefined cast functions accessible via cast_to. These functions cover frequent operations such as UnixTimestampToDate and IntToBool.

• The transformation logic has been significantly refactored, making transformers more customizable and flexible than before.

• Introduced transformation engines

  • random - generates transformer values based on pseudo-random algorithms.
  • hash - generates transformer values using hash functions. Currently, it utilizes sha3 hash functions, which are secure but perform slowly. In the stable release, there will be an option to choose between sha3 and SipHash.

• Introduced static parameters value template

Notable changes

Core

• Introduced the Parametrizer interface, now implemented for both dynamic and static parameters.
• Renamed most of the toolkit types for enhanced clarity and comprehensive documentation coverage.
• Refactored the Driver initialization logic.
• Added validation warnings for overridden types in the Driver.
• Migrated existing built-in transformers to utilize the new Parametrizer interface.
• Implemented a new abstraction, TransformationContext, as the first step towards enabling new feature transformation conditions (Feature: conditional transform #34).
• Optimized most transformers for performance in both dynamic and static modes. While dynamic mode offers flexibility, static mode ensures performance remains high. Using only the necessary transformation features helps keep transformation time predictable.

Documentation

Documentation has been significantly refactored. New information about features and updates to transformer descriptions have been added.

Transformers

• RandomEmail - Introduces a new transformer that supports both random and deterministic engines. It allows for flexible email value generation; you can use column values in the template and choose to keep the original domain or select any from the domains parameter.

• NoiseDate, NoiseFloat, NoiseInt - These transformers support both random and deterministic engines, offering dynamic mode parameters that control the noise thresholds within the min and max range. Unlike previous implementations which used a single ratio parameter, the new release features min_ratio and max_ratio parameters to define noise values more precisely. Utilizing the hash engine in these transformers enhances security by complicating statistical analysis for attackers, especially when the same salt is used consistently over long periods.

• NoiseNumeric - A newly implemented transformer, sharing features with NoiseInt and NoiseFloat, but specifically designed for numeric values (large integers or floats). It introduces a precision parameter to handle values with fractions.

• RandomChoice - Now supports the hash engine, enhancing its utility and security.

• RandomDate, RandomFloat, RandomInt - Now enhanced with hash engine support. Threshold parameters min and max have been updated to support dynamic mode, allowing for more flexible configurations.

• RandomNumeric - A new transformer specifically designed for numeric types (large integers or floats), sharing similar features with RandomInt and RandomFloat, but tailored for handling huge numeric values.

• RandomString - Now supports hash engine mode, enhancing its utility for generating secure, random strings.

• RandomUnixTimestamp - This new transformer generates Unix timestamps with selectable units (second, millisecond, microsecond, nanosecond). Similar in function to RandomDate, it supports the hash engine and dynamic parameters for min and max thresholds, with the ability to override these units using min_unit and max_unit parameters.

• RandomUuid - Enhanced with hash engine support, this transformer now offers even greater security for UUID generation.

• RandomPerson - Implemented a new transformer that replaces RandomName, RandomLastName, RandomFirstName, RandomFirstNameMale, RandomFirstNameFemale, RandomTitleMale, and RandomTitleFemale. This new transformer offers enhanced customizability while providing similar functionalities as the previous versions. It generates personal data such as FirstName, LastName, and Title, based on the provided gender parameter, which now supports dynamic mode. Future minor versions will allow for overriding the default names database.

• Added tsModify - a new template function that enhances parameter customization.

• Introduced a new RandomIp transformer capable of generating a random IP address based on the specified netmask.

• Launched a new RandomMac transformer for generating random Mac addresses.

• Deleted transformers include RandomMacAddress, RandomIPv4, RandomIPv6, RandomUnixTime, RandomTitleMale, RandomTitleFemale, RandomFirstName, RandomFirstNameMale, RandomFirstNameFemale, RandomLastName, and RandomName due to the introduction of more flexible and unified options.

Contributors

@dev-comrade
@wwoytenko

---

This discussion was created from the release v0.2.0b1.

[wwoytenko]

UPD:

If you want to run a Greenmask playground for the beta version execute

git checkout tags/v0.2.0b1 -b v0.2.0b1

docker-compose run greenmask-from-source