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CompTIA CY0-001 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Basic AI Concepts Related to Cybersecurity	17%	- AI-driven threats and risks 1. Automated phishing, polymorphic malware 2. Malicious use of generative AI 3. Adversarial machine learning attacks - AI applications in security 1. Threat detection and anomaly analysis 2. Security automation and decision support - Core AI principles and terminology 1. Machine learning, deep learning, NLP, automation 2. Generative AI concepts and capabilities
Topic 2: AI-assisted Security	24%	- AI for threat detection and response 1. Automated incident triage and correlation 2. Accelerated threat hunting 3. Anomaly detection and behavioral analysis - Security automation and orchestration 1. Workflow automation and response playbooks 2. Vulnerability management and assessment - AI in security strategy and operations 1. Threat modeling and risk assessment 2. Compliance monitoring and auditing
Topic 3: Securing AI Systems	40%	- Secure AI development and operations 1. DevSecOps integration for AI 2. Secure MLOps and AI pipeline design - Security controls for AI systems 1. Deployment environment security 2. Data protection: integrity, confidentiality, privacy 3. Model security: access, integrity, anti-tampering - Defending against AI-specific attacks 1. Threat modeling for AI lifecycles 2. Adversarial example defense 3. Prompt injection, data poisoning, model inversion
Topic 4: AI Governance, Risk and Compliance	19%	- Compliance and legal requirements 1. Data protection and privacy laws 2. Transparency, accountability and auditability - Risk management for AI 1. AI risk identification and assessment 2. Risk mitigation and control strategies - Governance frameworks and policies 1. Responsible AI principles and ethics 2. Global standards: NIST AI RMF, EU AI Act 3. Organizational AI governance structures

CompTIA SecAI+ Certification Sample Questions:

Question #1

A cybersecurity analyst wants to choose a machine learning (ML) model to classify log entries while providing the best explainability.
Which of the following models should the analyst use?

A. Neural networks
B. Generative adversarial network (GAN)
C. Decision trees
D. Large language model (LLM)

Reveal Solution Discussion 0

Correct Answer: C 🗳️