CYB 213 – Generative AI Privacy & Cybersecurity Risk (UPDATED)

Course Overview

As organizations adopt Generative AI technologies at scale, the associated cybersecurity and privacy risks are expanding just as rapidly. In response, global regulatory and standards bodies, including NIST, OWASP, and the EU’s GDPR, have released guidance to help secure AI systems and protect sensitive data.

This course provides Cyber Defense teams with a deep dive into the unique attack vectors and vulnerabilities introduced by Large Language Models (LLMs), such as ChatGPT, and the broader Generative AI ecosystem. Learners will gain practical skills to proactively secure AI systems, safeguard privacy, and ensure responsible AI adoption in compliance with leading global standards.

After completing this course, learners will have the knowledge and skills to identify and mitigate cybersecurity risks associated with Generative AI, including:

• Prompt Injection
• System Prompt Leakage
• Data Poisoning
• Improper Output Handling
• Model Theft
• Model Inversion
• Excessive Implementation
• Insecure Plugin Integration
• Detection Bypass
• Malware Generation
• Over-reliance on LLM Outputs
• Unbounded Resource Consumption
• Vector and Embedding Weaknesses
• Supply Chain Vulnerabilities