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CompTIA CY0-001 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: 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. Model security: access, integrity, anti-tampering 3. Data protection: integrity, confidentiality, privacy - Defending against AI-specific attacks 1. Prompt injection, data poisoning, model inversion 2. Adversarial example defense 3. Threat modeling for AI lifecycles
Topic 2: AI-assisted Security	24%	- AI in security strategy and operations 1. Threat modeling and risk assessment 2. Compliance monitoring and auditing - Security automation and orchestration 1. Vulnerability management and assessment 2. Workflow automation and response playbooks - AI for threat detection and response 1. Anomaly detection and behavioral analysis 2. Automated incident triage and correlation 3. Accelerated threat hunting
Topic 3: AI Governance, Risk and Compliance	19%	- Risk management for AI 1. Risk mitigation and control strategies 2. AI risk identification and assessment - Governance frameworks and policies 1. Organizational AI governance structures 2. Responsible AI principles and ethics 3. Global standards: NIST AI RMF, EU AI Act - Compliance and legal requirements 1. Data protection and privacy laws 2. Transparency, accountability and auditability
Topic 4: Basic AI Concepts Related to Cybersecurity	17%	- Core AI principles and terminology 1. Generative AI concepts and capabilities 2. Machine learning, deep learning, NLP, automation - 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

CompTIA SecAI+ Certification Sample Questions:

Question #1
Which of the following is the first step before using an online data set?

A. A feasibility study by the business
B. A model design review by the architect
C. A third-party risk management assessment
D. A review by the legal team

Question #2
A security consultant must summarize the impact of posture management on a machine learning (ML) use case.
Which of the following is the most appropriate reference for this purpose?

A. National Institute of Standards and Technology (NIST) AI Risk Management Framework (RMF)
B. Generative adversarial network (GAN)
C. European Union AI Act
D. Organization for Economic Co-operation and Development (OECD) standards

Question #3
Which of the following is used to train an AI model with unstructured data?

A. Statistical learning
B. Supervised learning
C. Fine-tuning
D. Reinforcement training

Question #4
Users report that the output of a generative AI application seems unrelated to the prompts and contains offensive content. A security team investigates and determines that there was an on-path attack.
Which of the following is the most likely attack method?

A. Session hijacking
B. Model hijacking
C. Application server hijacking
D. Domain hijacking

Question #5
Which of the following is an example of how a security analyst uses generative AI in the triage process?

A. To summarize security findings by category
B. To use statistical analysis for malicious code assessment
C. To predict the next attack target with higher accuracy
D. To tag malware using machine learning (ML) algorithms

Solutions:

Question #1
Correct Answer: C

Question #2
Correct Answer: A

Question #3
Correct Answer: C

Question #4
Correct Answer: A

Question #5
Correct Answer: A