Skip to main content

🧪 DISKOVERY: Disk Forensics Tool for Data Categorization & Keyword Filtering

DISKOVERY is a Python-based digital forensics tool designed to analyze disk images. It performs a multi-stage forensic analysis including imaging, partition parsing, file categorization, keyword-based filtering, and automatic PDF reporting. The tool supports both complete and filtered analysis outputs and provides investigators with a concise overview of disk contents. It is a command-line interface (CLI) tool that works well on Ubuntu and Debian-based systems.


⚙️ Features

  • Disk Image Support (.img, .E01, .dd)
  • Partition Parsing using mmls
  • File Categorization:
    • Deleted
    • Encrypted
    • Current
    • Hidden
  • File Type Filtering (e.g., .pdf, .docx)
  • Keyword Search in extracted text-based files
  • Visual Summary via pie charts
  • PDF Report Generation with listings, and visualizations

Steps to use

  1. Insert pendrive.
  2. To check the location at which it's inserted: sudo fdisk -l
  3. Go to script folder and run main.py: sudo python3 main.py

📁 Project Structure

diskovery/
├── diskovery/                       # Main package
│   ├── __init__.py
│   ├── main.py                      # CLI entry point
│   ├── stages/                      # Stage-wise modular pipeline
│   │   ├── __init__.py
│   │   ├── stage1_disk_imaging.py
│   │   ├── stage2_extraction.py
│   │   ├── stage3_categorization.py
│   │   ├── stage4_filtering.py
│   │   ├── stage4_2_keyword.py
│   │   └── stage5_reporting.py
│   └── utils/                       # Utility functions
│       ├── __init__.py
│       └── run_command.py
│
├── README.md                        # Project overview and usage
├── LICENSE                          # MIT License
├── setup.py                         # Packaging configuration
├── requirements.txt                 # Python dependencies
├── MANIFEST.in                      # Include non-code files for PyPI
├── pyproject.toml                   # Build configuration
└── .gitignore                       # Git ignore rules

🚀 Quick Start

1. Clone the Repository

git clone https://github.com/simmithapad/DISKOVERY.git
cd DISKOVERY

2. Run Setup (Installs Tools + Python Packages)

pip install -r requirements.txt

3. Start the Tool

python3 -m venv .venv
source .venv/bin/activate
python3 main.py

🛠️ Dependencies

System Tools (Installed via setup.sh)

  • dcfldd
  • sleuthkit (for mmls, fls, fsstat)
  • binwalk
  • grep and pdfgrep

Python Packages

  • fpdf
  • elasticsearch
  • docx2txt
  • re

📄 Output

  • Disk images saved in ./output_files/
  • PDF reports saved in ./output_files/reports/
  • Extracted files saved in ./output_files/extracted_files/

📬 Future Work

  • GPU Acceleration
  • Memory Forensics Integration

👤 Author

Simmi Thapad
Vrinda Abrol


License

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


🔒 Disclaimer

Metadata

Release files for diskovery 0.1.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for diskovery 0.1.2
File Size Uploaded Provenance Actions
diskovery-0.1.2.tar.gz 16.1 kB Without provenance Details for diskovery-0.1.2.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for diskovery 0.1.2
File Interpreter ABI Platform Actions
diskovery-0.1.2-py3-none-any.whl Python 3 none any Details for diskovery-0.1.2-py3-none-any.whl

Total release size: 32.9 kB

Release files / diskovery-0.1.2.tar.gz

Download URL diskovery-0.1.2.tar.gz
Size 16.1 kB
Tags Source
SHA-256 checksum
How to use checksums
89f649a056d932fddcd7d385d7df6b7607efe9a5e742995cc9ec1cbc474a470a
BLAKE2b-256 checksum
How to use checksums
3648e2ed5d47b3920e523c1d044cbe71499e3fb8f17d9f10ae86f6ca7f9b76bd
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.2

Release files / diskovery-0.1.2-py3-none-any.whl

Download URL diskovery-0.1.2-py3-none-any.whl
Size 16.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
08e60d4f176f1dcd6854abe6ae1ea2d0b9b0fd75b4ef3c43fbdc281e08ec9436
BLAKE2b-256 checksum
How to use checksums
3aff4a8a432c5e2b1ba8838a49db53ddacb28ad8d8057a125194e8b2e830f02c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.2

Security for diskovery 0.1.2

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page