Conseal

Abstract

1. Introduction

Python package, containing implementations of modern image steganographic algorithms.

2. Objective

Simulators of image steganography methods

This project demonstrates how Python can be applied to a real-world Cybersecurity & Ethical Hacking problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Python 3.8 or later
• pip / virtualenv for dependencies
• VS Code, PyCharm or Jupyter Notebook
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/uibk-uncover/conseal.git
cd conseal

1. J-UNIWARD
2. S-UNIWARD

pip3 install conseal

git clone https://github.com/uibk-uncover/conseal/
cd conseal
pip3 install .

import conseal as cl

# load cover
jpeg = jpeglib.read_dct("cover.jpeg")

# embed F5 0.4 bpnzAC
jpeg.Y = cl.F5.simulate_single_channel(
    y0=jpeg.Y,
    alpha=0.4,
    seed=12345)

# save result as stego image
jpeg.write_dct("stego.jpeg")

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Add logging and alert notifications (email / Telegram)
• Write a threat model document for the tool
• Package it with Docker for safe lab testing

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Which threat or attack does this project defend against?
2. What detection or protection technique is used and what are its limits?
3. How are false positives and false negatives handled?
4. Which cryptographic algorithms or security standards are involved?
5. What legal and ethical rules apply when testing a tool like this?

9. Source Code & License

This project is developed by uibk-uncover and published on GitHub under the Mozilla Public License 2.0. Please follow the license terms and credit the original author when you use or modify this code.