maskify-py 0.1.0

Maskify is a lightweight, efficient, and flexible library designed to help developers securely mask sensitive data such as Brazilian documents (CPF, CNPJ), emails, credit cards, mobile and residential phones, and more. It provides out-of-the-box masking for common data types and customizable masking options for any other sensitive information, ensuring compliance with data protection regulations like LGPD.

Maskify - Sensitive Data Masking Library for Python

Maskify is a lightweight, flexible library for Python, inspired by the Maskify.Core library for .NET. It helps developers securely mask sensitive data, such as Brazilian documents (CPF, CNPJ), emails, credit cards, and phone numbers. This library provides built-in masking for common data types, along with customizable masking options to ensure compliance with data protection regulations.

Features

• Mask CPF and CNPJ: Easily mask Brazilian CPF and CNPJ numbers.
• Email Masking: Partially mask email addresses.
• Credit Card Masking: Mask credit card numbers while preserving the last few digits.
• Phone Number Masking: Support for mobile and residential phone numbers.
• Custom Masking: Mask any string by specifying a start position, length, and masking character.

Installation

To install Maskify, run:

pip install maskify-py

Usage

Below are examples of using Maskify for different types of sensitive data.

1. Masking CPF

The CPF format consists of 11 digits. Maskify will retain the last two digits and mask the middle portion:

from maskify.masker import Masker

cpf = "123.456.789-01"
masked_cpf = Masker.mask_cpf(cpf, "X")
print(masked_cpf)  

# Output: "123.***.**9-01"

2. Masking CNPJ

The CNPJ format consists of 14 digits. Maskify will retain the first two and last two digits, masking the middle portion:

from maskify import mask_cnpj

cnpj = "12.345.678/0001-99"
masked_cnpj = Masker.mask_cnpj(cnpj, "X")
print(masked_cnpj)  

# Output: "12.XXX.XXX/XX01-99"

3. Masking Email

The email masking function hides a portion of the local part of the email (before @), leaving the first and last characters visible:

from maskify import mask_email

email = "[e-mail]"
masked_email = Masker.mask_email(email, "*")
print(masked_email)  

# Output: "u*****[e-mail]"

4. Masking Credit Card

Maskify supports multiple credit card formats, including standard 16-digit cards, American Express (15 digits), and Diners Club (14 digits). It retains only the last four digits, masking the rest:

from maskify import mask_credit_card

credit_card = "1234 1234 1234 1234"
masked_credit_card = Masker.mask_credit_card(credit_card, "*")
print(masked_card)  

# Output: "**** **** **** 1234"

5. Masking Mobile Phone Numbers

Mobile phone numbers with 11 digits are masked to display only the area code, first digit, and last four digits:

from maskify import mask_mobile_phone

mobile_phone = "(11) 91234-5678"
masked_mobile_phone = Masker.mask_mobile_phone(mobile_phone)
print(masked_phone)  

# Output: "(11) *****-5678"

6. Masking Residential Phone Numbers

Residential phone numbers with 10 digits are masked to display only the area code, first two digits, and last four digits:

from maskify import mask_residential_phone

residential_phone = "(11) 1234-5678"
masked_residential_phone = Masker.mask_residential_phone(residential_phone)
print(masked_phone)  

# Output: "(11) ****-5678"

7. Custom Masking

Maskify provides a general mask function to apply a mask to any string. Specify the start position, length of the mask, and masking character:

from maskify import mask

text = "1234567890"
masked_text = mask(text, start_position=2, length=4)
print(masked_text)  

# Output: "12****7890"

Error Handling

If input values do not meet format requirements, Maskify functions raise a ValueError with a descriptive message. Ensure that inputs are in the expected format (e.g., 11 digits for CPF, 14 digits for CNPJ) to avoid exceptions.

Contributing

We welcome contributions to enhance Maskify! Feel free to submit issues or pull requests. For major changes, please open a discussion first to share your proposed changes.

License

This project is licensed under the MIT License.