feat: Add AI Security module

[ykrishhh]

Summary

This PR adds a comprehensive AI Security module to the curriculum, addressing the growing need for security education in AI/ML development.

Changes

1. New Lesson: AI Security (lessons/8-Security/README.md)

   • Common AI security threats (model attacks, data attacks, infrastructure attacks)
   • Security best practices for ML development
   • Supply chain security
   • Adversarial robustness
   • Real-world case studies
   • References to OWASP ML Top 10 and other security frameworks

2. Hands-on Security Lab (lessons/8-Security/security_lab.ipynb)

   • Input validation exercises
   • Model integrity verification
   • Adversarial example generation
   • Secure model serialization
   • Security audit checklist

3. Updated README to include the new security module in the curriculum table

Why This Matters

As AI systems become more prevalent in production, security is no longer optional. This module teaches students to:

• Identify and mitigate common AI security threats
• Implement secure coding practices for ML
• Test adversarial robustness
• Apply supply chain security principles

Alignment

This content aligns with:

• OWASP Machine Learning Security Top 10
• NIST AI Risk Management Framework
• Microsoft's Responsible AI principles

Testing

• All code examples follow the existing curriculum structure
• Notebook includes practical exercises with clear learning objectives
• Content is beginner-friendly while covering essential security concepts

---

Closes #189 (if applicable)

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