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@Ronit26Mehta Ronit26Mehta released this 28 Mar 07:41
· 63 commits to main since this release
1.0.0
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Learn about vigilant mode.

v1.0 - Initial Release

Overview

This initial release introduces the User Data Capture PDF System, a comprehensive solution designed for forensic analysis and cybersecurity investigations. The system captures detailed client-side data during a PDF download, processes it using a Flask backend, and generates a PDF with embedded hidden data. This release is especially useful for internal investigations, including cases of harassment.

Key Features

  • Client-Side Data Capture

    • Collects screen dimensions, user-agent, canvas fingerprints, timing metrics, and more.
    • Utilizes an HTML/JavaScript form to gather data and populate hidden fields.

  • Server-Side Processing

    • Built on Flask, the system processes data, performs geolocation lookups via ipinfo.io, and securely logs interactions.
    • Generates a PDF using ReportLab with fake content provided by Faker to obfuscate real data.

  • PDF Generation with Embedded Security

    • Embeds an image containing encrypted, hidden data via steganography.
    • Integrates custom metadata and JavaScript callbacks to verify token-based access.

  • Encryption & Steganography

    • Encrypts collected data using Fernet to ensure confidentiality.
    • Uses Least Significant Bit (LSB) techniques to hide encrypted information within an image.

  • Verification & Callback Mechanisms

    • Implements token generation and verification for secure PDF access.
    • Tracks PDF openings via embedded JavaScript callbacks, ensuring a robust forensic audit trail.

  • Simulated Payloads for Testing

    • Demonstrates multi-stage payload processing and DLL injection simulations for enhanced system testing.

Forensic & Cybersecurity Considerations

  • Chain-of-Custody & Data Integrity: Secure logging and timestamping ensure that all captured data remains untampered for forensic analysis.
  • Audit and Monitoring: Detailed logging and callback verifications create a comprehensive audit trail critical for investigating internal harassment or other security incidents.

Usage

  1. Installation:

    • Ensure Python 3.x is installed.
    • Install required dependencies: 
      pip install flask reportlab pypdf2 cryptography stegano faker pillow requests

  2. Running the Application:

  3. Operation:

    • Use the provided download page to trigger PDF generation.
    • The system will capture client data, generate the PDF with hidden encrypted data, and log all interactions.
    • Opened PDFs trigger JavaScript callbacks to verify tokens and log access.

Documentation

Detailed technical documentation is provided in the accompanying LaTeX report and includes:

  • System architecture diagrams (component, sequence, activity, use-case, and optional deployment diagrams).
  • Comprehensive breakdown of data collection, PDF generation, encryption, steganography, and callback processes.
  • Forensic analysis and cybersecurity considerations.
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