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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Attacks, Threats, and Vulnerabilities | 24% | - Given a scenario, analyze potential indicators associated with application attacks - Compare and contrast types of social engineering attacks - Explain penetration testing concepts - Explain vulnerability scanning concepts - Explain threat actor types and attributes - Given a scenario, analyze potential indicators to determine the type of attack - Given a scenario, analyze potential indicators associated with network attacks |
| Topic 2: Architecture and Design | 21% | - Explain the security implications of embedded and specialized systems - Explain the importance of physical security controls - Summarize authentication and authorization design concepts - Summarize basics of cryptographic concepts - Summarize virtualization and cloud security concepts - Explain the importance of security concepts in an enterprise environment - Explain secure application development, deployment, and automation concepts - Given a scenario, implement cybersecurity resilience |
| Topic 3: Governance, Risk, and Compliance | 14% | - Summarize regulations, standards, and frameworks that impact organizations - Explain privacy and sensitive data concepts in relation to security - Given a scenario, follow organizational security policies and procedures - Compare and contrast various types of security controls - Explain risk management processes and concepts |
| Topic 4: Operations and Incident Response | 16% | - Explain key aspects of digital forensics - 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 - Given a scenario, use appropriate tool to assess organizational security |
| Topic 5: Implementation | 25% | - Given a scenario, implement secure systems design - Given a scenario, apply cybersecurity solutions to the cloud - Given a scenario, implement authentication and authorization solutions - Given a scenario, implement public key infrastructure (PKI) - Given a scenario, implement secure host settings - Given a scenario, implement secure network architecture concepts - Given a scenario, implement secure mobile device policies - Given a scenario, implement identity and account management controls |
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NEW QUESTION # 97
Which of the following requires developers to harden infrastructure to protect AI systems?
Answer: B
Explanation:
Basic Concept: Infrastructure hardening for AI systems involves applying security baseline settings and eliminating unnecessary attack surfaces. CompTIA SecAI+ Exam Objectives identify configuration standards as the specific governance instrument that mandates infrastructure hardening requirements for AI deployments.
Why D is Correct: Configuration standards are formal, technical documents specifying exact security settings, baseline configurations, and hardening requirements that developers and administrators must implement to protect systems including AI infrastructure. They establish enforceable rules such as disabling unnecessary services, applying least-privilege access, and enforcing secure communication protocols specifically for AI systems.
Why A is Wrong: Intake processes govern how new projects, systems, or requests are evaluated and onboarded into an organization. They are procedural checkpoints for initial assessment, not technical hardening directives for developers.
Why B is Wrong: Acceptable use policies define appropriate ways employees and users may use organizational systems and AI tools. They are behavioral guidelines aimed at end users, not technical requirements instructing developers to secure infrastructure.
Why C is Wrong: Development guidelines provide best practices and recommendations for software development and may include security considerations. However, they are advisory in nature and broader in scope than the specific mandatory infrastructure-hardening requirements found in configuration standards.
NEW QUESTION # 98
A detection engineering team wants to use AI to automatically prevent vulnerable code from reaching production. Which of the following is the most effective way to accomplish this task?
Answer: A
Explanation:
Integrating an LLM into the CI/CD pipeline ensures automated code review at build time, blocking vulnerable code from reaching production. This enforces security checks consistently and effectively during the deployment process.
NEW QUESTION # 99
Which are indicators of lateral movement? (Choose two.)
Answer: A,E
Explanation:
Lateral movement often involves internal SMB attacks and credential reuse.
NEW QUESTION # 100
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: D
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 # 101
A vulnerability scan produces many false positives. What does this indicate?
Answer: B
Explanation:
High sensitivity → catches many issues but lowers accuracy (more false positives).
NEW QUESTION # 102
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