CompTIA SecAI+ Boot Camp

SecAI+ (V1) exam objectives summary

Basic AI concepts related to cybersecurity (17%)

• Explain core AI principles and terminology: Machine learning, deep learning, natural language processing, and automation.

• Identify AI applications in security: Use cases for AI in threat detection, defense, and security operations. 

• Recognize AI-driven threats: Automated phishing, polymorphic malware, adversarial machine learning, and malicious use of generative AI.

Securing AI systems (40%)

• Implement security controls: Protect AI systems, data, and models using robust technical safeguards. 

• Secure AI deployment environments: Apply best practices across on-premises, cloud, and hybrid infrastructures. 

• Mitigate adversarial risks: Defend against attacks targeting AI models, data pipelines, and inference layers. 

AI-assisted security (24%)

• Enhance detection and response: Use AI-driven tools to identify anomalies, detect threats, and accelerate incident remediation. 

• Automate security workflows: Integrate AI for event triage, alert correlation, and response orchestration. 

• Apply AI techniques in operations: Incorporate AI into threat modeling, behavior analysis, and continuous monitoring. 

AI governance, risk, and compliance (19%)

• Understand regulatory frameworks: Identify global governance requirements and their implications for AI adoption. 

• Integrate GRC into AI projects: Incorporate governance, risk management, and compliance practices throughout the AI lifecycle. 

• Ensure responsible AI use: Apply ethical guidelines, legal standards, and industry frameworks such as GDPR and NIST AI RMF.