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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Governance, Risk, and Compliance | 14% | - Compare and contrast various types of security controls - Explain privacy and sensitive data concepts in relation to security - Explain risk management processes and concepts - Summarize regulations, standards, and frameworks that impact organizations - Given a scenario, follow organizational security policies and procedures |
| Topic 2: Architecture and Design | 21% | - Explain secure application development, deployment, and automation concepts - Summarize basics of cryptographic concepts - Explain the security implications of embedded and specialized systems - Given a scenario, implement cybersecurity resilience - Summarize authentication and authorization design concepts - Explain the importance of physical security controls - Summarize virtualization and cloud security concepts - Explain the importance of security concepts in an enterprise environment |
| Topic 3: Attacks, Threats, and Vulnerabilities | 24% | - Explain threat actor types and attributes - Compare and contrast types of social engineering attacks - Given a scenario, analyze potential indicators to determine the type of attack - Given a scenario, analyze potential indicators associated with application attacks - Explain vulnerability scanning concepts - Explain penetration testing concepts - Given a scenario, analyze potential indicators associated with network attacks |
| Topic 4: Operations and Incident Response | 16% | - Summarize the importance of policies, processes, and procedures for incident response - Given a scenario, apply mitigation techniques or controls to secure an environment - Given a scenario, use appropriate tool to assess organizational security - Given a scenario, use data sources to support an investigation - Explain key aspects of digital forensics |
| Topic 5: Implementation | 25% | - Given a scenario, implement secure systems design - Given a scenario, implement identity and account management controls - Given a scenario, implement authentication and authorization solutions - Given a scenario, implement secure host settings - Given a scenario, apply cybersecurity solutions to the cloud - Given a scenario, implement secure network architecture concepts - Given a scenario, implement secure mobile device policies - Given a scenario, implement public key infrastructure (PKI) |
With the ever-increasing competition, people take CompTIA CY0-001certification to exhibit their experience, skills, and abilities in a better way. Having CompTIA SecAI+ Certification Exam CY0-001 certificate shows that you have better exposure than others. So, CY0-001 Certification also gives you an advantage in the industry when employers seek candidates for job opportunities. However, preparing for the CompTIA CY0-001 exam can be a difficult and time-consuming process.
NEW QUESTION # 134
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 # 135
User experience is declining since the launch of a large language model (LLM) in internal networks. Which of the following should be the highest priority for the prompt engineers?
Answer: B
Explanation:
When user experience is declining after an LLM launch, the top priority for prompt engineers is quality control. Ensuring prompts produce accurate, relevant, and safe outputs directly improves usability and restores user trust.
NEW QUESTION # 136
During an update, an AI system flags some potential compatibility issues and provides recommendations. An administrator reviews the recommendations before addressing the issues.
Which of the following processes describes this scenario?
Answer: B
Explanation:
Basic Concept: Human-in-the-loop is a design pattern where AI systems generate recommendations or decisions but require human review and approval before those recommendations are acted upon. This approach maintains human oversight and accountability in AI-assisted workflows. CompTIA SecAI+ Study Guide covers human-in-the-loop as a key responsible AI principle and operational pattern.
Why C is Correct: The scenario precisely describes the human-in-the-loop pattern: the AI system identifies potential issues and provides recommendations, but an administrator must review those recommendations before any action is taken. This deliberate inclusion of human judgment in the AI ' s decision or recommendation workflow ensures human oversight is maintained, which is the defining characteristic of the human-in-the-loop process.
Why A is Wrong: Data validation verifies that data meets expected quality standards and formats before being used in AI processing. It is a data quality control activity, not a workflow pattern describing human review of AI recommendations.
Why B is Wrong: Data preparation involves transforming raw data into a format suitable for AI model training or inference. It encompasses cleaning, normalizing, and formatting data, not the process of human review of AI-generated recommendations during system updates.
Why D is Wrong: Model evaluation assesses a model ' s performance against metrics such as accuracy, precision, and recall on test datasets. It is a technical assessment of model quality, not a workflow process where humans review AI-generated recommendations before acting on them.
NEW QUESTION # 137
A security architect performs threat modeling of an AI system. The architect needs to determine which attacks can be performed against the system.
Which of the following actions should the architect take next?
Answer: B
Explanation:
Basic Concept: AI-specific threat modeling requires consulting resources that catalogue adversarial attacks specifically developed for AI and ML systems. General cybersecurity frameworks may miss AI-unique attack vectors such as model inversion, data poisoning, and adversarial examples. CompTIA SecAI+ Study Guide identifies MITRE ATLAS as the authoritative source for AI system TTPs.
Why D is Correct: MITRE ATLAS provides a comprehensive, curated knowledge base of adversarial tactics, techniques, and procedures specifically targeting AI and ML systems, derived from real-world attack case studies. Analyzing ATLAS enables the architect to enumerate realistic AI-specific attacks applicable to the system being threat-modeled, which directly answers the question of which attacks can be performed.
Why A is Wrong: Using an LLM to map attack paths introduces uncertainty and potential hallucination risk.
LLMs may generate plausible-sounding but inaccurate attack paths and cannot guarantee comprehensive coverage of AI-specific attack techniques.
Why B is Wrong: Quantifying risk of known vulnerabilities is a risk assessment step that occurs after identifying which attacks are possible. The architect must first identify attack possibilities before quantifying their risk impact.
Why C is Wrong: OWASP Top 10 covers web application vulnerabilities and, in its LLM edition, certain LLM-specific risks. However, MITRE ATLAS provides a more comprehensive and structured catalog of AI and ML-specific adversarial TTPs for systematic threat modeling.
NEW QUESTION # 138
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 # 139
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