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CompTIA CY0-001 Exam Syllabus Topics:

SectionWeightObjectives
AI Governance, Risk and Compliance19%- Governance frameworks and policies
  • 1. Organizational AI governance structures
  • 2. Responsible AI principles and ethics
  • 3. Global standards: NIST AI RMF, EU AI Act
- Risk management for AI
  • 1. AI risk identification and assessment
  • 2. Risk mitigation and control strategies
- Compliance and legal requirements
  • 1. Transparency, accountability and auditability
  • 2. Data protection and privacy laws
AI-assisted Security24%- 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
- AI in security strategy and operations
  • 1. Compliance monitoring and auditing
  • 2. Threat modeling and risk assessment
Securing AI Systems40%- Defending against AI-specific attacks
  • 1. Adversarial example defense
  • 2. Threat modeling for AI lifecycles
  • 3. Prompt injection, data poisoning, model inversion
- Secure AI development and operations
  • 1. Secure MLOps and AI pipeline design
  • 2. DevSecOps integration for AI
- Security controls for AI systems
  • 1. Deployment environment security
  • 2. Data protection: integrity, confidentiality, privacy
  • 3. Model security: access, integrity, anti-tampering
Basic AI Concepts Related to Cybersecurity17%- AI applications in security
  • 1. Threat detection and anomaly analysis
  • 2. Security automation and decision support
- Core AI principles and terminology
  • 1. Generative AI concepts and capabilities
  • 2. Machine learning, deep learning, NLP, automation
- AI-driven threats and risks
  • 1. Malicious use of generative AI
  • 2. Automated phishing, polymorphic malware
  • 3. Adversarial machine learning attacks

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CompTIA SecAI+ Certification Exam Sample Questions (Q79-Q84):

NEW QUESTION # 79
A healthcare organization plans to deploy a chatbot for appointment scheduling and patient records. Which of the following is the first step a security administrator should take?

Answer: A

Explanation:
Before deploying an AI chatbot that will handle sensitive healthcare data, the first step is to conduct a risk assessment. This identifies potential threats, compliance requirements (such as HIPAA), and security gaps, ensuring proper controls are planned before implementation.


NEW QUESTION # 80
Customer feedback for an AI chatbot has a high-rate of non-answers, which is causing higher central processing unit (CPU) utilization.
Which of the following should be implemented?

Answer: A

Explanation:
Basic Concept: AI chatbots that generate non-answers - responses that do not actually address user questions
- consume CPU resources for processing without delivering value. This can indicate the model is attempting to generate responses for queries outside its knowledge domain or confidence threshold. CompTIA SecAI+ Study Guide covers AI performance optimization and response quality management.
Why B is Correct: Implementing a response confidence level threshold allows the chatbot to recognize when it lacks sufficient confidence to provide a meaningful answer and respond accordingly, either with a helpful redirect or a clear indication that it cannot answer the query. This reduces the costly processing cycles spent generating poor-quality non-answers, lowers CPU utilization from failed response generation, and improves customer experience by setting appropriate expectations rather than returning unhelpful responses.
Why A is Wrong: Guardrails filter content for safety and policy compliance. They prevent harmful or out-of- policy responses but do not address the underlying issue of the model generating low-confidence non-answers to legitimate customer queries.
Why C is Wrong: Prompt logging records user inputs for analysis and auditing. While useful for identifying what types of questions cause non-answers, logging alone does not solve the problem or reduce CPU utilization from failed response generation.
Why D is Wrong: Cost monitoring tracks AI system expenditure. It can identify that costs are high due to excessive CPU usage but does not implement a solution to reduce the non-answer rate or improve response generation efficiency.


NEW QUESTION # 81
A penetration tester is assessing the controls of a deployed AI system that is designed to search and return the contents of files.
The tester runs the following:

Which of the following is the best control to prevent abuse of the system?

Answer: C

Explanation:
Basic Concept: AI systems that access file systems or databases use service accounts to authenticate.
Applying the principle of least privilege to these service accounts limits the damage that can result from prompt injection or other attacks that cause the AI to perform unauthorized file access. CompTIA SecAI+ Study Guide covers least privilege as a core AI security control.
Why D is Correct: Reducing the privilege scope of the service account implements the least privilege principle, ensuring the AI system can only access files it legitimately needs for its intended function. If an attacker uses prompt injection to abuse the file search capability, the service account ' s limited permissions prevent access to sensitive files outside the defined scope, containing the blast radius of any exploitation.
Why A is Wrong: Custom detection rules identify anomalous behavior after it occurs. They are detective controls, not preventive controls. They do not stop an attacker from successfully abusing the system; they only alert after abuse has occurred.
Why B is Wrong: VPC segmentation isolates the workload at the network level, limiting lateral movement.
However, it does not restrict what files the AI ' s service account can access within its own environment, so file abuse attacks within the segment are still possible.
Why C is Wrong: LLM guardrails filter prompt inputs and outputs for policy violations. While useful, they can potentially be bypassed through sophisticated prompt injection. Reducing service account privileges provides a defense-in-depth layer that limits damage even if guardrails are bypassed.


NEW QUESTION # 82
Which of the following is the best example of an AI model that is trained to identify multiple points from input using a neural network to provide output for authentication?

Answer: B

Explanation:
Basic Concept: Neural networks can be trained to identify and match complex multi-point patterns in data.
For biometric authentication, facial recognition uses deep neural networks to extract and compare dozens to hundreds of facial feature points from an input image. CompTIA SecAI+ covers neural network-based authentication under basic AI concepts.
Why A is Correct: Facial recognition systems use neural networks specifically trained to identify multiple facial landmarks and feature points such as eye distance, nose shape, and jawline contour from input images.
These extracted feature vectors are compared against stored templates to authenticate individuals, making this the ideal example of multi-point neural network-based authentication output.
Why B is Wrong: An encryption key is a cryptographic artifact, not an AI model output. Encryption keys are generated mathematically, not through neural network training or multi-point feature identification from biometric inputs.
Why C is Wrong: OAuth is an open authorization protocol framework that handles delegated access and permission grants between services. It is an authentication delegation standard, not an AI model that processes input through neural networks.
Why D is Wrong: A bounding box is an output of object detection models that draws a rectangular box around detected objects in an image. While it uses neural networks, it identifies object location rather than multiple feature points for authentication purposes.


NEW QUESTION # 83
An AI-based human resources system screens resumes to select the most suitable candidate for an interview.
The system recommends mostly male candidates. Which of the following responsible AI concepts does this system violate?

Answer: B


NEW QUESTION # 84
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