What you'll learn

AI systems create new security challenges across models, prompts, data, agents, application programming interfaces, and third-party integrations. In this course, Securing AI Systems for CompTIA SecAI+, you'll learn how to identify AI-specific threats and apply practical controls that reduce risk in enterprise environments. First, you'll explore AI threat modeling resources, including the OWASP LLM and Machine Learning Security Top 10, the MIT AI Risk Repository, MITRE ATLAS, the CVE AI Working Group, and established threat modeling frameworks. Next, you'll learn how to implement model and gateway controls, protect access to models, data, agents, networks, and APIs, and secure sensitive information through encryption, anonymization, classification, redaction, masking, and data minimization. Finally, you'll discover how to monitor prompts, responses, logs, usage rates, costs, quality, and compliance. You'll also analyze evidence of attacks such as prompt injection, poisoning, model theft, insecure output handling, excessive agency, and sensitive information disclosure, then select appropriate compensating controls. When you're finished with this course, you'll have the skills and knowledge needed to threat model AI systems, implement layered security controls, investigate AI-focused attacks, and prepare for Domain 2.0 of the CompTIA SecAI+ CY0-001 certification exam.