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CompTIA CY0-001 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI-assisted Security24%- Security automation and orchestration
  • 1. Vulnerability management and assessment
  • 2. Workflow automation and response playbooks
- AI in security strategy and operations
  • 1. Threat modeling and risk assessment
  • 2. Compliance monitoring and auditing
- AI for threat detection and response
  • 1. Anomaly detection and behavioral analysis
  • 2. Automated incident triage and correlation
  • 3. Accelerated threat hunting
Topic 2: 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. Adversarial example defense
  • 2. Prompt injection, data poisoning, model inversion
  • 3. Threat modeling for AI lifecycles
- Security controls for AI systems
  • 1. Deployment environment security
  • 2. Data protection: integrity, confidentiality, privacy
  • 3. Model security: access, integrity, anti-tampering
Topic 3: AI Governance, Risk and Compliance19%- Governance frameworks and policies
  • 1. Responsible AI principles and ethics
  • 2. Organizational AI governance structures
  • 3. Global standards: NIST AI RMF, EU AI Act
- Risk management for AI
  • 1. Risk mitigation and control strategies
  • 2. AI risk identification and assessment
- Compliance and legal requirements
  • 1. Transparency, accountability and auditability
  • 2. Data protection and privacy laws
Topic 4: Basic AI Concepts Related to Cybersecurity17%- Core AI principles and terminology
  • 1. Machine learning, deep learning, NLP, automation
  • 2. Generative AI concepts and capabilities
- AI applications in security
  • 1. Security automation and decision support
  • 2. Threat detection and anomaly analysis
- AI-driven threats and risks
  • 1. Adversarial machine learning attacks
  • 2. Automated phishing, polymorphic malware
  • 3. Malicious use of generative AI

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CompTIA SecAI+ Certification Exam Sample Questions (Q146-Q151):

NEW QUESTION # 146
An employee wants a consulting company to procure a data set that contains age, ethnicity, and diabetes status. During development, the employer wants to ensure the integrity of the data.
Which of the following is the best strategy to accomplish this task?

Answer: C

Explanation:
Checksums ensure data integrity by detecting any unauthorized or accidental changes to the dataset. This provides a reliable way to confirm that sensitive attributes such as age, ethnicity, and diabetes status remain unaltered during development.


NEW QUESTION # 147
An administrator, who works for a financial institution, is required to implement data security controls for data at rest within AI systems that involve data disclosure. Which of the following is the most suitable control?

Answer: C

Explanation:
For financial institutions handling AI systems, protecting data at rest against disclosure requires encryption. Encryption ensures that even if the storage medium is accessed or compromised, the data remains unreadable without the proper decryption keys.


NEW QUESTION # 148
Which control BEST prevents attackers from harvesting password hashes during lateral movement?

Answer: B

Explanation:
LSASS-protection solutions prevent hash extraction.


NEW QUESTION # 149
A machine learning (ML) engineer is working with a security engineer to identify the best practices for securing a system with various AI models.
Which of the following actions should the engineers suggest?

Answer: B

Explanation:
A secure MDLC is tailored to AI and ML systems, ensuring security is integrated throughout the model's design, training, validation, deployment, and monitoring phases. This directly addresses best practices for securing systems with AI models.


NEW QUESTION # 150
Which of the following would most likely be used to prove that an image is AI generated?

Answer: D

Explanation:
Basic Concept: As AI-generated images become increasingly indistinguishable from authentic photographs, technical mechanisms are needed to definitively identify synthetic content. Embedding verifiable markers in AI-generated content at creation time provides a reliable provenance trail. CompTIA SecAI+ Study Guide covers digital content authentication and AI provenance controls.
Why D is Correct: Watermarking embeds invisible or visible identifying markers into AI-generated images at the point of creation. These watermarks can be cryptographic, steganographic, or perceptual in nature and survive compression, cropping, and other common image manipulations. When an image ' s provenance is questioned, watermark detection tools can analyze it to confirm AI generation. This is the primary technical mechanism for proving AI image origin as supported by the Content Authenticity Initiative and C2PA standards.
Why A is Wrong: Human validation relies on subjective visual inspection by experts to determine if an image appears AI-generated. Modern AI image generation has advanced to the point where human reviewers frequently cannot distinguish synthetic from authentic images, making this approach unreliable for definitive proof.
Why B is Wrong: Guardrails are input and output filtering controls for AI systems. They restrict what content an AI can generate but do not create verifiable proof of an image ' s AI origin after generation.
Why C is Wrong: Diffusion refers to the diffusion model architecture used to generate images. It describes the creation process, not a verification mechanism. Knowing that diffusion models were used does not help prove a specific image was AI-generated after the fact.


NEW QUESTION # 151
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