This Python script 'deanonymizes' sensitive info in documents. The script uses aliases for sensitive names. When ran, the deanonymization script replaces the alias with the sensitive name. The names and aliases are read from a CSV file.
- Python 3.8 or later
- Docker
- Clone this repository to your local machine.
- Ensure that Docker is installed and running on your machine.
From the project directory, run:
docker build -t deanonymize .
This command builds a Docker image named deanonymize using the Dockerfile in the current directory (.).
After building the Docker image, you can run the Docker container with this command:
docker run -it -v /path/to/your/documents_and_csv/:/app/ -u $(id -u):$(id -g) deanonymize python ./deanonymize.py /app/your_documents_directory /app/your_csv_file
In the docker run command:
-v /path/to/your/documents_and_csv/:/app/mounts your directory to/app/in the Docker container.-u $(id -u):$(id -g)runs the command in the Docker container as the current user, which helps to avoid permission issues.deanonymizeis the name of the Docker image to run.python ./deanonymize.py /app/your_documents_directory /app/your_csv_fileis the command to run in the Docker container. Replaceyour_documents_directorywith the path to your documents directory inside the Docker container andyour_csv_filewith the name of your CSV file inside the Docker container.
Remember to replace /path/to/your/documents_and_csv/, your_documents_directory, and your_csv_file with your actual paths and filenames.
Please ensure that the deanonymize.py script and the CSV file are both located in the /path/to/your/documents_and_csv/ directory on your host machine.
This script assumes that 'names_and_aliases.csv' is the CSV file with the names and aliases and that your_documents_directory is the directory with the documents. If your CSV file is not in the same directory as your documents, you will need to modify the -v option to mount the CSV file in the correct location in the container.