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| Section | Weight | Objectives |
|---|---|---|
| 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 - Given a scenario, use data sources to support an investigation - Summarize the importance of policies, processes, and procedures for incident response - Explain key aspects of digital forensics |
| Architecture and Design | 21% | - Explain the importance of physical security controls - Summarize authentication and authorization design concepts - Explain the importance of security concepts in an enterprise environment - Summarize virtualization and cloud security concepts - Given a scenario, implement cybersecurity resilience - Explain the security implications of embedded and specialized systems - Explain secure application development, deployment, and automation concepts - Summarize basics of cryptographic concepts |
| Implementation | 25% | - Given a scenario, implement identity and account management controls - Given a scenario, apply cybersecurity solutions to the cloud - Given a scenario, implement secure network architecture concepts - Given a scenario, implement secure host settings - Given a scenario, implement public key infrastructure (PKI) - Given a scenario, implement secure systems design - Given a scenario, implement secure mobile device policies - Given a scenario, implement authentication and authorization solutions |
| Attacks, Threats, and Vulnerabilities | 24% | - Explain vulnerability scanning concepts - Explain penetration testing concepts - Given a scenario, analyze potential indicators to determine the type of attack - Explain threat actor types and attributes - Given a scenario, analyze potential indicators associated with application attacks - Given a scenario, analyze potential indicators associated with network attacks - Compare and contrast types of social engineering attacks |
| 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 |
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NEW QUESTION # 37
After the latest software update, a developer receives reports that the system no longer requires reauthentication to display account balances because this issue was present in a previous release. Which of the following should the developer do to best mitigate the risk of recurrence?
Answer: B
Explanation:
Option B is correct because the defect is a regression: a security behavior that should require reauthentication was previously corrected but reappeared after a software update. Automated AI-assisted regression testing in the CI/CD pipeline can repeatedly verify that protected account-balance functions still demand reauthentication before a release is promoted. The test should reproduce the prior defect, fail the build when authentication is bypassed, and preserve the case as a permanent security test. Option A adds an approval step, but an approver may not detect the reintroduced behavior without an executable test. Option C improves release scheduling and traceability but does not prove that security controls still function. Option D uses SAST to inspect source code for known weakness patterns; it may identify some authentication flaws, but it does not reliably validate the end-to-end runtime behavior described here. Regression testing is the direct control for preventing recurrence. The NIST AI Risk Management Framework emphasizes testing AI systems before deployment and regularly during operation, supporting automated security validation within the delivery pipeline.
NEW QUESTION # 38
A recently deployed AI system becomes persistently unavailable. A restart temporarily fixes the issue, but the issue happens again. Upon examination of application programming interface (API) logs, an analyst finds that external calls continued to use system resources after the action completed.
Which of the following is the best way to improve availability of the system?
Answer: B
Explanation:
The persistent unavailability is caused by external calls consuming resources even after completion, indicating sessions are not being closed. Enforcing session expiration ensures unused sessions are terminated, freeing resources and improving system availability.
NEW QUESTION # 39
A management team is concerned about an unexpected cost increase for a public-facing AI chatbot.
Which of the following should a security administrator examine first to determine the root cause?
Answer: C
Explanation:
Basic Concept: AI chatbot operational costs are primarily driven by token consumption - the number of tokens processed in requests and generated in responses. Unexpected cost increases in LLM-based chatbots almost always trace back to abnormal token usage patterns. CompTIA SecAI+ Study Guide covers AI cost monitoring and token-based billing under securing AI systems.
Why D is Correct: Model token usage logs directly show how many tokens are being consumed per request, by which users or endpoints, and whether usage has increased abnormally. Examining token usage data is the most direct path to identifying the root cause of unexpected cost increases - whether from a denial-of-wallet attack, user abuse, a new feature generating verbose responses, or legitimate organic growth in usage. This is the first and most relevant examination point for LLM cost analysis.
Why A is Wrong: Firewall logs capture network-level traffic information. While they can reveal unusual access patterns or volumes, they do not contain token consumption data that directly explains LLM billing increases.
Why B is Wrong: WAF rules define filtering policies for web traffic. Reviewing rule configurations does not reveal whether token usage has increased or why costs have risen; it shows security policy settings rather than consumption metrics.
Why C is Wrong: Vector database IOPS performance measures how quickly the database processes read and write operations. While relevant to RAG system performance, IOPS metrics do not directly explain LLM API cost increases driven by token consumption.
NEW QUESTION # 40
An administrator must conduct generative AI cost monitoring for use in the healthcare industry.
Which of the following criteria is the best way to calculate this cost?
Answer: D
Explanation:
Basic Concept: Generative AI systems in healthcare settings incur costs from multiple operational activities.
Understanding the cost drivers specific to generative AI helps administrators implementaccurate cost monitoring and controls. CompTIA SecAI+ Study Guide covers AI cost management under securing AI systems.
Why C is Correct: Storage retrieval and prompt processing are the two primary cost drivers for generative AI systems in healthcare. Storage retrieval refers to the cost of querying vector databases or document stores in RAG-based AI systems to fetch relevant patient records, clinical guidelines, or historical data for context.
Prompt processing encompasses the token-based cost of the LLM processing the combined retrieved content and user query to generate a response. Together these two activities represent the billable units that drive generative AI costs in healthcare RAG deployments, making them the most accurate basis for cost calculation and monitoring.
Why A is Wrong: Connection access and exchange gateway costs relate to network infrastructure and API gateway usage fees. While there may be minor costs associated with API calls, these are not the primary cost drivers for generative AI systems where the dominant expenses are computational token processing and data retrieval operations.
Why B is Wrong: Encryption and decryption processing costs relate to cryptographic operations for data security. While encryption is important for healthcare data protection under HIPAA, cryptographic processing overhead is minimal compared to the substantial token-based LLM processing and storage retrieval costs that dominate generative AI operational expenses.
Why D is Wrong: Catalog servicing and exchange processing are terms associated with data catalog management and data exchange infrastructure. These are not recognized primary cost components of generative AI systems in healthcare, where storage retrieval and token-based prompt processing are the established cost measurement criteria.
NEW QUESTION # 41
Which of the following technologies is used in deepfake?
Answer: B
Explanation:
Deepfakes are primarily created using GANs, where two neural networks (a generator and a discriminator) compete to produce highly realistic synthetic media, such as manipulated videos or images.
NEW QUESTION # 42
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