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CompTIA CY0-001 Exam Syllabus Topics:

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

CompTIA SecAI+ Certification Sample Questions:

Question #1

A manufacturing company wants to use AI within its operations to improve the efficiency and accuracy of its processes.
Which of the following should the organization do first to enable adoption and achieve the business objectives?

A. Hire a data and AI architect.
B. Select a large language model (LLM).
C. Introduce a generative adversarial network (GAN).
D. Achieve International Organization for Standardization (ISO) 42001 certification.

Reveal Solution Discussion 0

Correct Answer: A 🗳️

Explanation: Only visible for Test4Engine members. You can sign-up / login (it's free).

Question #2

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

Reveal Solution Discussion 0

Correct Answer: A 🗳️

Explanation: Only visible for Test4Engine members. You can sign-up / login (it's free).

Question #3

A data scientist investigates reports that a production machine learning (ML) model no longer performs with accuracy.
The data scientist finds the following pipeline log entries:

Which of the following should the security team do to mitigate future occurrences?

A. Enable human review and approval workflows in the repository.
B. Retrain the model on using increased data and epochs.
C. Keep multiple copies of the model for restoration.
D. Add static code scanning tooling to the runner job.

Reveal Solution Discussion 0

Correct Answer: A 🗳️

Explanation: Only visible for Test4Engine members. You can sign-up / login (it's free).

Question #4

User experience is declining since the launch of a large language model (LLM) in internal networks.
Which of the following should be the highest priority for the prompt engineers?

A. Quality control
B. Customer success management
C. Business objectives
D. Sales life cycle

Reveal Solution Discussion 0

Correct Answer: A 🗳️

Explanation: Only visible for Test4Engine members. You can sign-up / login (it's free).

Question #5

A team of engineers builds an application using a large language model (LLM). The application is built on Linux and is hosted on a virtual server. Users must create an account in order to access and use the platform.
Which of the following should the team do to protect the account credentials?