Aperi Solve

Abstract

1. Introduction

Aperi'Solve is an open-source steganalysis web platform that performs automated analysis on images to detect and extract hidden data using common steganography tools and techniques.

steganography handbook — a triage methodology, a decision-tree cheatsheet, technique pages per medium (image, audio, text, files), and a guide per analyzer, all authored as Markdown.

Russian, Chinese and Portuguese under language-prefixed URLs (/fr/, /es/, …).

2. Objective

Steganalysis web platform

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

3. Key Features / Modules

• Visualize each bit layer (LSB and other layers) per image channel (R/G/B/Alpha).
• Color remapping (random palette remaps with 8 generated variants)
• Runs 16 analyzers in parallel and displays their output, with per-tool
• binwalk (embedded archives)
• exiftool (metadata and geolocation)
• file (MIME type and format detection)
• GraphicsMagick identify (image info & properties)
• foremost (carved files)
• jsteg (JPEG LSB extraction)
• jpseek / jphide (JPEG steganography extraction, with password)

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/Zeecka/AperiSolve.git
cd AperiSolve

git clone https://github.com/Zeecka/AperiSolve.git
cd AperiSolve
cp .env.example .env
docker compose up -d

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 Zeecka and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.