- Complete threat landscape analysis (data poisoning, prompt injection, model theft)
- Practical governance frameworks for AI systems
- Step-by-step implementation guide (24-week roadmap)
- Risk assessment methodologies specific to AI
- Incident response playbooks for AI compromises
- Real case studies with lessons learned
- Actionable 30/90/365-day plans
🎯 Key Features:
- Practical Focus: Real-world solutions, not just theory
- Comprehensive Coverage: Technical, operational, and business aspects
- Implementation Ready: Detailed timelines, checklists, and templates
- Future-Proof: Addresses emerging threats and technologies
The guide is structured to help organizations immediately begin securing their AI systems while building long-term resilience. It's written for both technical teams and business leaders who need to understand and address AI security risks.
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