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CompTIA CY0-001 Exam Syllabus Topics:

SectionWeightObjectives
Basic AI Concepts Related to Cybersecurity17%- AI applications in security
  • 1. Threat detection and anomaly analysis
  • 2. Security automation and decision support
- AI-driven threats and risks
  • 1. Automated phishing, polymorphic malware
  • 2. Adversarial machine learning attacks
  • 3. Malicious use of generative AI
- Core AI principles and terminology
  • 1. Generative AI concepts and capabilities
  • 2. Machine learning, deep learning, NLP, automation
AI-assisted Security24%- AI for threat detection and response
  • 1. Accelerated threat hunting
  • 2. Anomaly detection and behavioral analysis
  • 3. Automated incident triage and correlation
- 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
AI Governance, Risk and Compliance19%- 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
Securing AI Systems40%- Secure AI development and operations
  • 1. DevSecOps integration for AI
  • 2. Secure MLOps and AI pipeline design
- Defending against AI-specific attacks
  • 1. Prompt injection, data poisoning, model inversion
  • 2. Threat modeling for AI lifecycles
  • 3. Adversarial example defense
- Security controls for AI systems
  • 1. Deployment environment security
  • 2. Data protection: integrity, confidentiality, privacy
  • 3. Model security: access, integrity, anti-tampering

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CompTIA SecAI+ Certification Exam Sample Questions (Q102-Q107):

NEW QUESTION # 102
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?

Answer: C

Explanation:
In an on-path attack, an adversary intercepts and manipulates traffic between the user and the AI system. Session hijacking allows the attacker to inject or alter prompts and responses, leading to unrelated or offensive output.


NEW QUESTION # 103
An organization is concerned with the exposure of sensitive data. Which of the following is the most relevant security concern?

Answer: B

Explanation:
Model inversion is a security concern where attackers can reconstruct or infer sensitive training data from the AI model's outputs. This directly threatens data confidentiality, making it the most relevant concern for sensitive data exposure.


NEW QUESTION # 104
A short AI-generated video shows a celebrity's likeness talking about a fake public security event.
Which of the following was used to create this video?

Answer: B

Explanation:
Convolutional neural networks (CNNs) are commonly used in generating deepfake videos, where a person's likeness is realistically mapped and animated to create fake but convincing audiovisual content.


NEW QUESTION # 105
Which of the following is required first in order to send a prompt query and response in a language model (LLM) system when authentication is enabled?

Answer: B

Explanation:
Basic Concept: When authentication is enabled on an LLM system, users must prove their identity before the system processes any requests. The authentication process must occur at the point where users first attempt to access the system before any data can be transmitted. CompTIA SecAI+ Study Guide covers the order of authentication controls in AI system access architectures.
Why B is Correct: Endpoint access control is the first requirement when authentication is enabled, as it governs the initial connection from the user ' s device to the system. Before any prompt can be sent or response received, the endpoint must be authenticated and authorized to access the LLM service. Endpoint access control verifies user identity and device compliance at the earliest possible point in the request flow, gating all subsequent processing.
Why A is Wrong: A front-end web proxy gateway routes and manages web traffic between users and backend services. While it may participate in the authentication flow, it is a routing and mediation component that operates after the endpoint has been validated, not the first authentication requirement.
Why C is Wrong: An API gateway manages API traffic, authentication tokens, and rate limiting for API interactions. It processes requests after initial endpoint authentication has been established and the request is being routed to the LLM backend.
Why D is Wrong: A back-end access gateway controls access to backend services and resources. It operates downstream from both endpoint authentication and API gateway processing, representing a deeper layer of the access control architecture rather than the first authentication requirement.


NEW QUESTION # 106
A security analyst who is reviewing logs notices the following:
* Suspicious inputs are present and contain character look-alikes.
* Strange character substitutions
* Odd spacing
* Inputs that appear to be broken sentence structures
Which of the following best explains what the user was utilizing?

Answer: C

Explanation:
Obfuscation is the correct answer because the observed inputs show deliberate attempts to make content difficult for automated security controls or AI systems to interpret while preserving enough meaning for the intended recipient. Character look-alikes, unusual Unicode substitutions, abnormal spacing, and deliberately fragmented sentence structures are common techniques for disguising malicious or restricted content.
CompTIA SecAI+ explicitly identifies obfuscation within the AI-assisted security domain as a way AI can enable or enhance attack vectors.
Disinformation involves intentionally spreading false information to deceive an audience, while misinformation refers to inaccurate information that may be distributed without deliberate malicious intent.
Neither term describes manipulating the representation of text to evade detection. Anonymization removes or obscures identifying information to protect identity or privacy; it does not explain character substitution or malformed sentence construction. In this scenario, the attacker is manipulating how the input appears so filtering, pattern-matching, or other inspection mechanisms may have difficulty recognizing the underlying content. Therefore, obfuscation most precisely describes the activity.


NEW QUESTION # 107
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