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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Architecture and Design | 21% | - Explain the importance of physical security controls - Explain secure application development, deployment, and automation concepts - Summarize basics of cryptographic concepts - Summarize authentication and authorization design concepts - Summarize virtualization and cloud security concepts - Explain the importance of security concepts in an enterprise environment - Explain the security implications of embedded and specialized systems - Given a scenario, implement cybersecurity resilience |
| Topic 2: Attacks, Threats, and Vulnerabilities | 24% | - Given a scenario, analyze potential indicators associated with application attacks - Given a scenario, analyze potential indicators to determine the type of attack - Compare and contrast types of social engineering attacks - Explain penetration testing concepts - Explain vulnerability scanning concepts - Given a scenario, analyze potential indicators associated with network attacks - Explain threat actor types and attributes |
| Topic 3: Implementation | 25% | - Given a scenario, implement secure host settings - Given a scenario, implement secure systems design - Given a scenario, apply cybersecurity solutions to the cloud - Given a scenario, implement public key infrastructure (PKI) - Given a scenario, implement secure mobile device policies - Given a scenario, implement secure network architecture concepts - Given a scenario, implement identity and account management controls - Given a scenario, implement authentication and authorization solutions |
| Topic 4: Governance, Risk, and Compliance | 14% | - Given a scenario, follow organizational security policies and procedures - Compare and contrast various types of security controls - Summarize regulations, standards, and frameworks that impact organizations - Explain privacy and sensitive data concepts in relation to security - Explain risk management processes and concepts |
| Topic 5: Operations and Incident Response | 16% | - Given a scenario, use appropriate tool to assess organizational security - Given a scenario, apply mitigation techniques or controls to secure an environment - Summarize the importance of policies, processes, and procedures for incident response - Given a scenario, use data sources to support an investigation - Explain key aspects of digital forensics |
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질문 # 123
An AI security team must assess the probability of an attack on its new system and the impact associated with such an attack. Which of the following threat-modeling resources best addresses the threat landscape for machine learning (ML)?
정답：A
설명：
MITRE ATLAS is specifically designed to capture adversarial tactics, techniques, and procedures (TTPs) targeting machine learning systems. It helps organizations assess both the probability and impact of AI/ML-related attacks, making it the most relevant threat-modeling resource.
질문 # 124
An organization develops a chatbot that does not provide harmful or explicit responses, must use clean and professional language, and ensures that responses are accurate.
Which of the following should the organization conduct after the chatbot is fully developed but before a customer-facing deployment?
정답：A
설명：
Basic Concept: Before deploying an AI chatbot that has specific behavioral requirements - no harmful content, professional language, and accurate responses - organizations must verify that the controls designed to enforce these requirements actually work as intended. This pre-deployment verification is essential for customer-facing systems. CompTIA SecAI+ Study Guide covers guardrail testing as a required pre- deployment activity.
Why C is Correct: Guardrail testing and validation specifically verifies that the content filtering, safety controls, and behavioral constraints implemented in the chatbot function correctly before customer exposure.
This involves systematically testing with edge cases, adversarial prompts, and boundary conditions to confirm that harmful content is blocked, language remains professional, and responses are accurate. This directly validates the three requirements stated in the question.
Why A is Wrong: Data labeling and classification is a data preparation activity performed during model training and development. By the time the chatbot is fully developed, this work should already be complete.
Why B is Wrong: Model auditing and evaluation assesses overall model performance, accuracy, and compliance at a broader level. While important, it does not specifically verify that the guardrails enforcing the three behavioral requirements work correctly for the specific failure modes customers might trigger.
Why D is Wrong: Regression modeling and minimization refers to statistical techniques for continuous outcome prediction. This is not a relevant pre-deployment activity for a conversational chatbot requiring behavioral safety validation.
질문 # 125
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?
정답：C
설명：
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.
질문 # 126
An architect is creating a threat model for an agentic system.
Which of the following should the architect do first?
정답：B
설명：
Basic Concept: Threat modeling for any system, and especially for agentic AI systems with multiple interacting components, begins with understanding the system ' s architecture and where trust boundaries exist. Trust boundaries define where data and control flows cross between components with different trust levels, representing potential attack surfaces. CompTIA SecAI+ Study Guide aligns with STRIDE and MITRE ATLAS threat modeling methodologies.
Why B is Correct: Identifying trust boundaries between components is the foundational first step in threat modeling. Agentic systems often involve multiple components such as the orchestrator, tools, APIs, data sources, and external services with different trust levels. Understanding where these boundaries exist reveals where untrusted inputs cross into trusted components, enabling the architect to systematically identify threats at each boundary before proceeding to risk quantification and control application.
Why A is Wrong: Applying compensating controls based on exposure findings is the final step in threat modeling, occurring after threats have been identified and risks quantified. Controls cannot be appropriately designed without first understanding the system ' s trust boundaries and threat landscape.
Why C is Wrong: Calculating risk to resources based on data sensitivity is a risk assessment step that occurs after trust boundaries are mapped and potential threats are identified. Risk quantification requires knowing what threats exist at each boundary first.
Why D is Wrong: Scanning for OWASP Top 10 vulnerabilities is a technical vulnerability assessment activity. While valuable, it comes after the architectural analysis of trust boundaries and threat identification phases of threat modeling.
질문 # 127
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?
정답：A
설명：
Basic Concept: Data at rest refers to inactive data stored in databases or storage media. Protecting it from unauthorized disclosure is a fundamental data security principle covered in the CompTIA SecAI+ Study Guide under securing AI data pipelines.
Why C is Correct: Encryption protects data at rest by rendering it unreadable to unauthorized parties without the appropriate decryption key. In a financial institution with sensitive data, encryption at rest (e.g., AES-256) is the primary control against data disclosure. Even if storage media is physically compromised, encrypted data remains unintelligible. CompTIA SecAI+ Exam Objectives highlight encryption as the primary confidentiality control for stored AI data.
Why A is Wrong: Data lineage tracks the origin and movement of data throughout its lifecycle. It improves traceability and auditability but does not prevent unauthorized disclosure of data at rest.
Why B is Wrong: Rate limits control the number of API requests within a time period. They protect against abuse and denial-of-service scenarios, not data-at-rest confidentiality.
Why D is Wrong: Data masking replaces sensitive values with fictitious substitutes, useful during development or testing. For actual production data at rest in AI systems handling real financial records, encryption provides stronger and more comprehensive confidentiality.
질문 # 128
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