data-anonymization | Want to use production data for testing | DB Client library

by sunitparekh Ruby Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | data-anonymization Summary

data-anonymization is a Ruby library typically used in Utilities, DB Client, Docker applications. data-anonymization has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Afraid of using production data due to privacy issues? Data Anonymization is a tool that helps you build anonymized production data dumps which you can use for performance testing, security testing, debugging and development.

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Support

data-anonymization has a low active ecosystem.

It has 432 star(s) with 96 fork(s). There are 21 watchers for this library.

It had no major release in the last 6 months.

There are 28 open issues and 30 have been closed. On average issues are closed in 202 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of data-anonymization is current.

Quality

data-anonymization has 0 bugs and 0 code smells.

Security

data-anonymization has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

data-anonymization code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

data-anonymization is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

data-anonymization releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

data-anonymization saves you 1315 person hours of effort in developing the same functionality from scratch.

It has 2950 lines of code, 179 functions and 126 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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data-anonymization Key Features

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data-anonymization Examples and Code Snippets

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Community Discussions

Trending Discussions on data-anonymization

Data masking in relational table using R

ProxySQL data masking for multiple columns

QUESTION

Data masking in relational table using R

Asked 2020-Oct-13 at 07:47

I am trying to mask data in such a way that referential integrity is not compromised.

My table Customer has this data:

Customer table

...

ANSWER

Answered 2020-Sep-01 at 18:32

There are two things that seem important for you

anonymity
referential integrity

For both of your requirements that solution from the blog article you linked is a bad choice.

Anonymity

Just hashing does not provide anonymity. The article also mentions (but it is not in the code) you probably at least want to add a salt.

Just an example:

A number like 211 will be af9fad5f as a CRC32 hash. If the person you share your data with sees this 8char(32bit) alphanumeric string it probably will assume that this might be a CRC32 hash. The good thing with hashes is you can not easily calculate back starting from af9fad5f to 211. The bad thing is, most short words/ hashes are already precalculated and easy to look up in what is called a rainbow table (e.g. https://md5hashing.net/hash/crc32/af9fad5f).

This basically means everybody could just look up the "clear text" behind the crc32 hashes. (same for all other hashes). Adding a salt prevents this. (this salt must of course be kept secret!)

Referential Integrity The referential integrity is kept. 211 will be always be af9fad5f as a CRC32 hash - this is static and there is no random effect to it. So the Product_ID would stay the same for all your tables. Which is what you need.

But just to be sure I would use SHA256 instead of CRC32. In CRC32 everything will be mapped to a 8chars alphanumeric (32bit). If you have quite a lot of data - there is some chance of hash collisions. This means two numbers/ids in the same table actually having the same hash. With SHA256 this is next to impossible.

Overall I think using the anonymizer package seems ok. (it is not actively maintained - but functionality seems to be ok)

Source https://stackoverflow.com/questions/63619978

QUESTION

ProxySQL data masking for multiple columns

Asked 2019-Mar-18 at 05:27

I want to mask sensitive information on multiple columns in a table named my_table using ProxySQL.

I've followed this tutorial to successfully mask a single column named column_name in a table using the following mysql_query_rules:

...

ANSWER

Answered 2019-Mar-18 at 05:27

Using flagIN, flagOUT, and apply allows me to mask data on multiple columns.

Here's the final mysql_query_rules I have: