MongoMasker

MongoMasker is a tool designed to anonymize specified fields in a MongoDB collection. It uses the faker library to generate realistic fake data, processes documents in batches for improved performance, and leverages asynchronous processing with motor for efficiency.

Features

• Anonymizes specified fields with realistic fake data
• Supports nested fields and fields within objects in arrays
• Processes documents in batches for better performance
• Uses asynchronous processing for efficiency
• Allows warnings for missing fields or unsupported structures

Requirements

• Python 3.6+
• motor library
• pymongo library
• faker library
• typer library

Installation

Install the required libraries using pip:

poetry install

Usage

Command-Line Example To anonymize fields in a MongoDB collection, run the following command:

mongomasker \
    "mongodb://your_username:your_password@your_host:your_port" \
    source_database \
    source_collection \
    target_database \
    target_collection \
    fields_to_anonymize.json \
    --batch-size 100 \
    --show-warnings \
    --mongo-filter '{"status": "active", "createdAt": {"$gt": "2023-01-01"}}'

Arguments

• mongo_uri: MongoDB connection URI (e.g., "mongodb://localhost:27017")
• source_db: Name of the source database
• source_collection: Name of the source collection
• target_db: Name of the target database
• target_collection: Name of the target collection
• fields_to_anonymize_file: Path to the JSON file specifying the fields to anonymize
• --batch-size: (Optional) Number of documents to process in each batch (default: 100)
• --show-warnings: (Optional) Show warnings for missing fields or unsupported structures
• --mongo-filter: (Optional) MongoDB filter as JSON string to filter source documents (default: "{}") Example fields_to_anonymize.json Create a JSON file specifying the fields to anonymize and their corresponding data types. For example:

{
    "name": "name",
    "email": "email",
    "address.street": "address",
    "address.city": "city",
    "address.zipcode": "zipcode",
    "user.stateCode": "statecode",
    "user.lastname": "lastname",
    "user.fullname": "lastnamefirstname",
    "createdAt": "date",
    "updatedAt": "datestr",
    "order.id": "id"
}

Explanation of Transformations

The fields_to_anonymize.json file maps field names to the type of fake data to generate. Below are examples of transformations for various data types:

Sample Workflow Prepare the fields_to_anonymize.json file: Create a JSON file specifying the fields to anonymize and their corresponding data types.

Run the MongoMasker CLI: Use the command-line tool to anonymize the data in the source collection and copy it to the target collection.

Verify the Results: Check the target collection to ensure the data has been anonymized as expected.

Example

Input Document (Source Collection)

{
    "_id": "12345",
    "name": "John Doe",
    "email": "john.doe@example.com",
    "address": {
        "street": "123 Main St",
        "city": "New York",
        "zipcode": "10001"
    },
    "user": {
        "stateCode": "NY",
        "lastname": "Doe",
        "fullname": "Doe, John"
    },
    "createdAt": "2023-01-01",
    "updatedAt": "2023-01-02",
    "order": {
        "id": "1234567890"
    }
}

Output Document (Target Collection)

{
    "_id": "12345",
    "name": "Alice Smith",
    "email": "alice@example.com",
    "address": {
        "street": "456 Elm St",
        "city": "Los Angeles",
        "zipcode": "90210"
    },
    "user": {
        "stateCode": "CA",
        "lastname": "Smith",
        "fullname": "Smith, Alice"
    },
    "createdAt": "2025-03-22",
    "updatedAt": "2025-03-22",
    "order": {
        "id": "9876543210"
    }
}

License

This project is licensed under the MIT License. See the LICENSE file for details.