Malware Ioc

Abstract

1. Introduction

This repository contains indicators of compromise (IOCs) of our various investigations.

2. Objective

This repository contains indicators of compromise (IOCs) of our various investigations.

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/prodaft/malware-ioc.git
cd malware-ioc

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 prodaft 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.