Generative AI – Risk and Cyber Security Masterclass 2025 Course Syllabus

Full curriculum breakdown — modules, lessons, estimated time, and outcomes.

Overview (80-120 words) describing structure and time commitment.

Module 1: Introduction to Generative AI Risks

Estimated time: 0.5 hours

  • Overview of Generative AI and its attack surface in cybersecurity
  • Understanding the expanding role of AI in digital threats
  • Key threat categories: prompt injection, model abuse, and adversarial inputs

Module 2: Deepfakes, Phishing & Misinformation

Estimated time: 0.75 hours

  • How GenAI tools can create deceptive content
  • Real-world phishing and impersonation examples
  • Detecting and defending against AI-generated misinformation
  • Case studies of social engineering powered by Generative AI

Module 3: Threat Modeling for AI Systems

Estimated time: 1 hour

  • Building threat models for GenAI applications
  • Identifying vulnerabilities unique to AI systems
  • Risk assessment tools and frameworks specific to AI
  • Applying STRIDE or DREAD models to AI pipelines

Module 4: Secure GenAI Development Practices

Estimated time: 1 hour

  • Coding and data practices to prevent model misuse
  • Input validation and output filtering strategies
  • Monitoring and alerting for anomalous AI behavior
  • Securing APIs and integration points in AI workflows

Module 5: Governance, Compliance & Auditing

Estimated time: 0.75 hours

  • Legal frameworks: GDPR, CCPA, and emerging AI regulations
  • Establishing accountability in AI deployment
  • Auditing GenAI systems for fairness, transparency, and security

Module 6: AI Risk Mitigation Strategy

Estimated time: 0.75 hours

  • Building organizational readiness for AI-related threats
  • Developing incident response plans for AI breaches
  • Training, policies, and cross-functional collaboration for defense
  • Creating AI security playbooks and escalation protocols

Prerequisites

  • Familiarity with basic cybersecurity concepts
  • Understanding of AI or machine learning fundamentals preferred
  • Interest in risk management or compliance frameworks

What You'll Be Able to Do After

  • Identify key cybersecurity risks associated with Generative AI
  • Analyze and respond to AI-driven threats like deepfakes and phishing
  • Apply threat modeling techniques to AI systems
  • Implement secure development practices in GenAI projects
  • Develop governance strategies and compliance audits for AI deployments
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