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CompTIA CY0-001 Exam Syllabus Topics:

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

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CompTIA SecAI+ Certification Exam Sample Questions (Q119-Q124):

NEW QUESTION # 119
An internal user enters a client credit card number into an internal generative machine learning (ML) model:
#User prompt: Customer Jane Doe has a new credit card that she wants to add to her account. The number is
5555-5555-5555-5555
Which of the following is the most effective way to prevent prompt injection attacks against a large language model (LLM)?

Answer: B

Explanation:
Basic Concept: Prompt injection occurs when malicious content embedded in user input manipulates an LLM
' s behavior, causing it to leak sensitive data, bypass restrictions, or execute unintended actions. Preventing such attacks requires mechanisms that inspect and filter content at the prompt level. CompTIA SecAI+ covers LLM-specific security controls extensively.
Why A is Correct: Guardrails are purpose-built controls that inspect, filter, and constrain both input prompts and output responses in LLM systems. They can detect sensitive data patterns such as credit card numbers, block prompt injection payloads, enforce content policies, and prevent the model from processing or outputting restricted information. Guardrails are the primary LLM-native defense against prompt injection as cited in the CompTIA SecAI+ Study Guide.
Why B is Wrong: Antivirus software detects known malware signatures in files and executables. It does not inspect or understand the semantic content of LLM prompts and cannot detect or block prompt injection attacks.
Why C is Wrong: A WAF operates at the HTTP layer inspecting web requests and responses against rule sets.
While it can block some patterns, it lacks the contextual intelligence to understand LLM prompt semantics and cannot prevent sophisticated injection attacks.
Why D is Wrong: Role-based access control manages who can access which resources. It controls authorization but does not inspect the content of prompts to prevent injection attacks once a user has legitimate access.


NEW QUESTION # 120
Instructions: Use the drop-down menus to define two appropriate security controls for each component of the AI system. Each control may be used only once.
An engineer is deploying a new AI system and wants to integrate it into the core system through an API.

Answer:

Explanation:

Explanation:

Basic Concept: This is a Performance-Based Question (PBQ) - a HOTSPOT/simulation item requiring interactive selection in the actual exam. It tests the candidate ' s ability to map appropriate security controls to AI system components such as API gateway, model endpoint, data layer, and authentication layer.
Key Concept - Appropriate Controls by Component: For an API gateway connecting an AI system, typical controls include API key authentication, rate limiting, TLS encryption, and input validation. For the model endpoint, controls include IAM role-based access, audit logging, and guardrails. For data access components, encryption at rest and data masking are appropriate. For the authentication layer, MFA and expiring session tokens are relevant.
Why This Matters: The CompTIA SecAI+ Study Guide emphasizes defense-in-depth for AI system integration, ensuring each architectural layer has dedicated, appropriate security controls. The principle of least privilege should guide access control assignments at each component, while availability controls such as rate limiting protect against abuse.
Reference: CompTIA SecAI+ Exam Objectives Domain 2 (Securing AI Systems) covers AI system component security controls. Candidates should study the mapping of controls to infrastructure components including API gateways, model serving endpoints, data stores, and identity management layers. In the live exam, select the most specific and directly relevant control for each component based on the component ' s function and risk profile.


NEW QUESTION # 121
Which of the following is an example of how a security analyst uses generative AI in the triage process?

Answer: C

Explanation:
In triage, generative AI is most effective for quickly summarizing and categorizing large volumes of alerts or findings. This helps analysts prioritize incidents and streamline the investigation process.


NEW QUESTION # 122
An organization wants to reduce vulnerabilities after deployment. The organization decides to incorporate an AI-assisted early detection and vulnerability identification process in its development workflow.
Which of the following AI-assisted functions is the best option?

Answer: A

Explanation:
Basic Concept: Reducing post-deployment vulnerabilities requires catching security issues as early as possible in the development workflow. AI-assisted tools that analyze code during development provide the earliest possible intervention point. CompTIA SecAI+ Study Guide covers AI integration in secure development under AI-assisted security.
Why A is Correct: AI-assisted code linting analyzes source code in real time during development to identify security vulnerabilities, insecure coding patterns, policy violations, and quality issues before code is compiled or committed. By catching vulnerabilities at the coding stage - the earliest possible point in the development workflow - AI code linting prevents vulnerable code from progressing to testing, staging, or production, directly reducing post-deployment vulnerabilities at their source.
Why B is Wrong: Incident management handles security events and incidents after they have occurred in production. It is a reactive capability focused on response and recovery rather than early-stage vulnerability identification in the development workflow.
Why C is Wrong: Automated deployment/rollback automates the process of pushing code to production and reverting to previous versions when issues are detected post-deployment. It is a deployment safety mechanism rather than an early detection tool during the development phase.
Why D is Wrong: System auditing reviews and records system activities and configurations for compliance verification. It is primarily a detective and compliance control for systems that are already deployed, not an early development-phase vulnerability identification tool.


NEW QUESTION # 123
A SOC analyst notices a sudden spike in outbound traffic from a server. The traffic is being sent continuously to an unknown external IP address. Which of the following BEST describes this behavior?

Answer: A

Explanation:
A sudden and sustained outbound transfer to an unknown IP is a common sign of data exfiltration.


NEW QUESTION # 124
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