diskovery 0.1.1

DISKOVERY: Disk Forensics Tool for Data Categorization & Keyword Filtering

🧪 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/
├── stages/
│   ├── __init__.py
│   ├── stage1_disk_imaging.py
│   ├── stage2_extraction.py
│   ├── stage3_categorization.py
│   ├── stage4_filtering.py
│   ├── stage4_2_keyword.py
│   └── stage5_reporting.py
├── utils/
│   ├── __init__.py
│   └── run_command.py
├── main.py
├── LICENSE
├── README.md
├── requirements.txt
├── setup.py
├── MANIFEST.in
└── pyproject.toml

---

🚀 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

[!Important] This tool is intended for educational and lawful forensic analysis only. Use responsibly.