Standard CY0-001 Answers | Test CY0-001 Objectives Pdf

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CompTIA CY0-001 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Basic AI Concepts Related to Cybersecurity17%- AI Threat Landscape
  • 1. Adversarial AI and model manipulation
    • 2. AI-driven cyber threats (phishing, malware automation)
      - AI and Machine Learning Fundamentals
      • 1. Neural networks and deep learning basics
        • 2. Supervised, unsupervised, reinforcement learning
          - Generative AI Concepts
          • 1. Prompting and AI interaction fundamentals
            • 2. LLMs and generative AI basics
              Topic 2: AI Governance, Risk, and Compliance19%- Risk and Compliance
              • 1. Regulatory compliance for AI systems
                • 2. Ethical AI and responsible usage policies
                  - AI Governance Frameworks
                  • 1. NIST AI RMF concepts
                    • 2. ISO/IEC AI governance alignment
                      Topic 3: Securing AI Systems40%- Adversarial Defense
                      • 1. Data poisoning mitigation
                        • 2. Model extraction and inference attack defense
                          - AI System Protection
                          • 1. Data protection and model security
                            • 2. Secure AI pipelines and deployment environments
                              Topic 4: AI-Assisted Security24%- Security Operations Enhancement
                              • 1. SOC automation and alert correlation
                                • 2. AI-driven threat detection and anomaly detection
                                  - Operational Use of AI
                                  • 1. Incident response acceleration
                                    • 2. AI-enabled threat intelligence analysis

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                                      CompTIA SecAI+ Certification Exam Sample Questions (Q106-Q111):

                                      NEW QUESTION # 106
                                      A security operations center (SOC) has a very high volume of logs and alerts. The manager proposes the implementation of a machine learning (ML) system to help with triage.
                                      Which of the following tasks is most suitable?

                                      Answer: C

                                      Explanation:
                                      Basic Concept: ML models excel at classification tasks, learning to assign incoming data points to predefined categories based on patterns in training data. In a SOC context, alert classification is the highest-value triage function ML can perform. CompTIA SecAI+ Exam Objectives address AI-assisted security operations under Domain 3.
                                      Why C is Correct: ML-based alert classification automatically analyzes characteristics of each alert and assigns it to a severity category such as critical, high, medium, or low, or to a threat type such as malware or intrusion attempt. This dramatically reduces analyst workload and speeds triage by prioritizing which alerts demand immediate human attention, directly solving the high-volume problem.
                                      Why A is Wrong: Applying filters on specific alerts is a rule-based operation achievable without ML using simple log management tools. It requires no learning capability and does not adapt to new or evolving threats.
                                      Why B is Wrong: Automatically patching systems is a remediation action requiring validated, controlled processes. Having an ML system autonomously patch production systems without human oversight poses unacceptable operational and security risk.
                                      Why D is Wrong: Summarizing alert content is a useful generative AI function but does not provide prioritization value for triage. Classification tells analysts what to act on first; summarization only rephrases existing information.


                                      NEW QUESTION # 107
                                      An AI security administrator notices that the information referenced by the model is incorrectly formatted and missing values. Which of the following job roles would most likely be responsible for correcting this error?

                                      Answer: C

                                      Explanation:
                                      A data engineer is responsible for preparing, cleaning, and formatting data pipelines. When information is incorrectly formatted or missing values, the data engineer ensures data integrity and quality before it is used by AI models.


                                      NEW QUESTION # 108
                                      An IT company implements an adaptable chatbot that learns from user prompts. Based on the conversation shown - where User 2 injected false information about a company acquisition that caused the chatbot to give incorrect responses to User 3 - which of the following compensating controls should an administrator implement to mitigate the issue?

                                      Answer: A


                                      NEW QUESTION # 109
                                      Which of the following attacks would be the best to automate with AI during dynamic application software testing (DAST)?

                                      Answer: C

                                      Explanation:
                                      During DAST, automating the generation of diverse, targeted attack payloads lets testers probe runtime inputs (e.g., XSS, SQLi, command injection) more thoroughly and discover vulnerabilities that manual or static tests might miss.


                                      NEW QUESTION # 110
                                      A vulnerability scan produces many false positives. What does this indicate?

                                      Answer: D

                                      Explanation:
                                      High sensitivity โ†’ catches many issues but lowers accuracy (more false positives).


                                      NEW QUESTION # 111
                                      ......

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