The Complete Course of Red Team 2025

Hands-on project ideas to practice and apply your learning

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Project Ideas
Hands-on practice
AI-Powered Phishing Detection System
Beginner 8h

Develop a basic AI model that can identify phishing emails by analyzing headers and content. This project introduces AI applications in cybersecurity for beginners.

Real-World Context: Phishing attacks are a common cybersecurity threat. This project simulates the development of a basic AI tool used by security teams to identify and mitigate such threats.
Learning Objectives
  • Understand the basics of AI and machine learning
  • Apply AI to detect cybersecurity threats
  • Develop a simple phishing detection system
Skills Practiced
Basic AI and machine learning Python programming
Deliverables
  • A functioning AI model for phishing detection
  • A report detailing the model's accuracy and limitations
  • A presentation explaining the project and results
Success Criteria
  • Model correctly identifies phishing emails with at least 70% accuracy
  • Comprehensive report on model performance
  • Clear and informative project presentation
Required Tools & Technologies
Python Scikit-learn
Concepts from Resource
AI in cybersecurity Threat detection
Project Type:

Individual

Industry Context:

Cybersecurity

Automated Threat Detection Workflow
Intermediate 8h

Create an automated workflow using security automation tools to detect and respond to common threats in a simulated network environment.

Real-World Context: Security teams often rely on automation to manage routine tasks and respond to threats quickly. This project mimics real-world scenarios where such workflows are essential.
Learning Objectives
  • Learn to use security automation tools
  • Design workflows for threat detection
  • Implement automation in a simulated network
Skills Practiced
Security automation Workflow design
Deliverables
  • An automated workflow in a security tool
  • Documentation of the workflow process
  • A demo video showcasing the workflow in action
Success Criteria
  • Workflow successfully detects and responds to simulated threats
  • Detailed documentation of the automation process
  • Engaging demo video with clear explanations
Required Tools & Technologies
Splunk Python
Concepts from Resource
Security automation Threat detection
Project Type:

Team

Industry Context:

Cybersecurity

Advanced AI-Driven Intrusion Detection System
Advanced 8h

Develop a comprehensive AI-driven intrusion detection system (IDS) using machine learning techniques to identify and respond to complex cyber threats.

Real-World Context: Organizations need sophisticated IDS to protect against advanced persistent threats. This project equips learners with the skills to develop cutting-edge IDS solutions.
Learning Objectives
  • Deepen understanding of AI applications in IDS
  • Develop advanced machine learning models for threat detection
  • Implement and test an AI-driven IDS
Skills Practiced
Advanced machine learning Intrusion detection system design
Deliverables
  • A fully functional AI-driven IDS
  • A technical report on model development and testing
  • A security policy document for IDS deployment
Success Criteria
  • IDS accurately detects complex threats with high precision
  • Comprehensive technical report with insights and improvements
  • Clear security policy for IDS deployment
Required Tools & Technologies
TensorFlow Keras Wireshark
Concepts from Resource
AI in cybersecurity Machine learning applications
Project Type:

Individual

Industry Context:

Cybersecurity

Projects Overview
Total:
3 projects
Beginner:
1
Intermediate:
1
Advanced:
1
Total Time:
~24 hours
Getting Started
  1. Start with beginner projects if you're new to the topic
  2. Review the resource material before beginning
  3. Set up the required tools and technologies
  4. Follow the learning objectives step by step
  5. Document your progress and learnings
  6. Share your completed projects for feedback
Resource Details
Type:
online_course
Difficulty:
intermediate
AI-Generated Content

These project ideas were generated using AI to provide practical, hands-on learning experiences based on the resource content.

Projects are designed to reinforce learning through real-world application and skill development.