p7m-extractor

Scripts to extract original documents from .P7M signed files.

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Table of Contents

1. About The Project
2. Features
3. Getting Started
   • Prerequisites
   • Installation
4. Usage
5. Roadmap
6. Contributing
7. License
8. Contact

About The Project

These scripts scan a specified directory for .P7M files (digitally signed containers) and extract the embedded PDF documents. They identify the PDF header within the P7M file and save the extracted content as a new PDF file.

Available implementations:

• PowerShell (Extract-P7M.ps1) - Windows-native solution
• Python (extract-p7m.py) - Cross-platform solution

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Features

• Extracts PDF files from P7M containers
• Supports recursive directory scanning
• Provides progress indication during processing
• Offers detailed mode with tabular output
• Validates input directory paths
• Includes comprehensive error handling with colored output

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Getting Started

Prerequisites

PowerShell Version

• Windows PowerShell 5.1 or later
• Execution policy allowing script execution (e.g., RemoteSigned)

Python Version

• Python 3.6 or later
• No additional dependencies required

Installation

1. Clone the repo

   git clone https://github.com/mantamburini/p7m-extractor.git
   

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Usage

PowerShell Script

.\Extract-P7M.ps1 [-Path <String>] [-Recurse] [-Detailed]

Parameters

• -Path <String>
  The directory path to scan for .P7M files. Defaults to the current working directory. Must be a valid container path.

• -Recurse <Switch>
  If specified, recursively scans subdirectories for .P7m files.

• -Detailed <Switch>
  If specified, provides detailed processing information in tabular format instead of simple console messages.

Examples

1. Extract PDFs from P7M files in the current directory:

   .\Extract-P7M.ps1
   

2. Extract PDFs from a specific directory:

   .\Extract-P7M.ps1 -Path "C:\MyDocuments"
   

3. Extract PDFs recursively from a directory:

   .\Extract-P7M.ps1 -Path "C:\MyDocuments" -Recurse
   

4. Extract PDFs with detailed tabular output:

   .\Extract-P7M.ps1 -Path "C:\MyDocuments" -Detailed
   

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Python Script

python extract-p7m.py [path] [-r] [-d]

Parameters

• path (optional)
  The directory path to scan for .P7M files. Defaults to the current working directory.

• -r, --recurse
  If specified, recursively scans subdirectories for .P7M files.

• -d, --detailed
  If specified, provides detailed processing information in tabular format.

Examples

1. Extract PDFs from P7M files in the current directory:

   python extract-p7m.py
   

2. Extract PDFs from a specific directory:

   python extract-p7m.py "/path/to/documents"
   

3. Extract PDFs recursively from a directory:

   python extract-p7m.py "/path/to/documents" -r
   

4. Extract PDFs with detailed tabular output:

   python extract-p7m.py "/path/to/documents" -d
   

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Output

PowerShell Version

• Without -Detailed: Displays colored "OK " (green) for successful extractions, warnings for files without PDFs, or red error messages for processing failures.
• With -Detailed: Outputs a table with columns: FileName, Status, OutputFile, Size. Exits early if no .p7m files are found.

Python Version

• Without -d: Displays "OK " for successful extractions, "NO PDF " for files without PDFs, or error messages for processing failures.
• With -d: Outputs a table with columns: FileName, Status, OutputFile, Size. Exits early if no .p7m files are found.

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Roadmap

See the open issues for a full list of proposed features (and known issues).

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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License

Distributed under the GPL-3.0 License. See LICENSE for more information.

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Contact

Marcello Anselmi Tamburini

Project Link: https://github.com/mantamburini/p7m-extractor

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