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| Section | Weight | Objectives |
|---|---|---|
| Implementation | 25% | - Given a scenario, apply cybersecurity solutions to the cloud - Given a scenario, implement identity and account management controls - Given a scenario, implement public key infrastructure (PKI) - Given a scenario, implement secure host settings - Given a scenario, implement secure systems design - Given a scenario, implement secure mobile device policies - Given a scenario, implement secure network architecture concepts - Given a scenario, implement authentication and authorization solutions |
| Governance, Risk, and Compliance | 14% | - Given a scenario, follow organizational security policies and procedures - Explain privacy and sensitive data concepts in relation to security - Compare and contrast various types of security controls - Explain risk management processes and concepts - Summarize regulations, standards, and frameworks that impact organizations |
| Attacks, Threats, and Vulnerabilities | 24% | - Explain vulnerability scanning concepts - Given a scenario, analyze potential indicators associated with network attacks - Explain penetration testing concepts - Given a scenario, analyze potential indicators to determine the type of attack - Given a scenario, analyze potential indicators associated with application attacks - Compare and contrast types of social engineering attacks - Explain threat actor types and attributes |
| Architecture and Design | 21% | - Given a scenario, implement cybersecurity resilience - Summarize authentication and authorization design concepts - Explain the importance of security concepts in an enterprise environment - Summarize virtualization and cloud security concepts - Summarize basics of cryptographic concepts - Explain the importance of physical security controls - Explain secure application development, deployment, and automation concepts - Explain the security implications of embedded and specialized systems |
| Operations and Incident Response | 16% | - Given a scenario, use appropriate tool to assess organizational security - Given a scenario, use data sources to support an investigation - Summarize the importance of policies, processes, and procedures for incident response - Given a scenario, apply mitigation techniques or controls to secure an environment - Explain key aspects of digital forensics |
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NEW QUESTION # 139
A human resources officer is using AI to evaluate resumes and help select candidates that meet minimum criteria. To improve the results, the human resources officer adjusts the query parameters and includes an example resume that matches a successful candidate.
Which of the following best describes this query?
Answer: D
Explanation:
Basic Concept: Prompting techniques determine how effectively an LLM is guided to produce desired outputs. Providing a single example within a prompt is a well-established technique known as one-shot prompting, which leverages in-context learning. CompTIA SecAI+ Study Guide covers prompting strategies under basic AI concepts.
Why C is Correct: One-shot prompting involves providing exactly one example of the desired input-output format within the prompt to guide the model ' s responses. In this scenario, the HR officer includes one example resume matching a successful candidate to show the model what a qualifying candidate looks like.
This single example instructs the model on the evaluation criteria through demonstration rather than explicit description.
Why A is Wrong: Distillation is a model training technique where a smaller student model is trained to replicate the behavior of a larger teacher model. It is a model compression methodology, not a prompting technique used at query time.
Why B is Wrong: A prompt template is a reusable, structured format for prompts with placeholders that can be filled in for different queries. While templates may incorporate examples, the term specifically describes the structural framework, not the act of providing a single example.
Why D is Wrong: A system role defines the AI model ' s persona, context, and behavioral guidelines at the system level before user interaction begins. It sets the model ' s overall behavior, not a specific technique of providing examples within queries.
NEW QUESTION # 140
An AI architect reviews AI utilization and wants to improve the user experience.
Which of the following should the architect review within the logs?
Answer: A
Explanation:
Basic Concept: User experience with AI systems is directly correlated to how accurately and relevantly the model responds to user queries. Poor model accuracy manifests as irrelevant, incorrect, or unhelpful responses, which is the primary driver of poor user experience. CompTIA SecAI+ Study Guide covers AI performance monitoring and user experience optimization.
Why B is Correct: Model accuracy metrics in logs reveal how often the model provides correct, relevant, and useful responses. Reviewing accuracy-related log data such as confidence scores, response quality ratings, error rates, and user feedback correlations enables the architect to identify performance gaps causing poor experiences and guides optimization efforts like fine-tuning or retrieval improvements.
Why A is Wrong: Rate monitoring tracks API call frequency and throughput. While important for capacity planning and detecting abuse, it does not directly reflect the quality of model responses that determine user experience.
Why C is Wrong: Access controls manage who can use the system and what permissions they have. They are a security concern rather than a user experience metric. Reviewing access control logs does not reveal information about response quality.
Why D is Wrong: Data storage metrics relate to storage capacity, utilization, and performance of data persistence layers. While these can affect response speed, they do not provide insights into model response quality or accuracy that drive user experience.
NEW QUESTION # 141
An automobile manufacturer implements a chatbot to assist with configuration options for customer automobiles. Given a customer ' s prompt, the chatbot gives offensive responses.
Which of the following describes this behavior?
Answer: B
NEW QUESTION # 142
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: B
Explanation:
A sudden and sustained outbound transfer to an unknown IP is a common sign of data exfiltration.
NEW QUESTION # 143
A legal firm permits employees to use a company-authorized chatbot for their research and reporting. In the past year, the firm had to retract some of its released documents because of incorrect references.
Which of the following best describes the weakness that caused this issue?
Answer: B
Explanation:
Overreliance occurs when users place excessive trust in AI-generated output without performing sufficient independent verification. The scenario indicates that employees used a chatbot for research and reporting and subsequently published documents containing incorrect references. That pattern strongly indicates that AI- generated citations or factual claims were accepted without adequate human validation. CompTIA SecAI+ explicitly lists overreliance among attacks and weaknesses that security professionals must recognize when analyzing AI systems. Generative AI systems can produce hallucinated or inaccurate citations that appear credible, which is why human oversight and human validation remain important lifecycle controls. Insecure output handling instead concerns unsafe downstream processing of model output, such as executing generated code or passing untrusted output into another system without validation. Excessive agency occurs when an AI system has more autonomous permissions or capabilities than necessary. Sensitive information disclosure involves exposing protected or confidential information. None of those conditions explains publication of believable but inaccurate references as directly as overreliance. Appropriate mitigation includes independent verification, authoritative-source validation, human review, and monitoring AI output for accuracy and hallucinations before publication.
NEW QUESTION # 144
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