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| Section | Weight | Objectives |
|---|---|---|
| Attacks, Threats, and Vulnerabilities | 24% | - Given a scenario, analyze potential indicators to determine the type of attack - Compare and contrast types of social engineering attacks - Explain penetration testing concepts - Given a scenario, analyze potential indicators associated with application attacks - Explain threat actor types and attributes - Given a scenario, analyze potential indicators associated with network attacks - Explain vulnerability scanning concepts |
| Operations and Incident Response | 16% | - Given a scenario, use appropriate tool to assess organizational security - Explain key aspects of digital forensics - Summarize the importance of policies, processes, and procedures for incident response - Given a scenario, use data sources to support an investigation - Given a scenario, apply mitigation techniques or controls to secure an environment |
| Implementation | 25% | - Given a scenario, implement secure network architecture concepts - Given a scenario, implement secure systems design - Given a scenario, implement secure mobile device policies - Given a scenario, implement public key infrastructure (PKI) - Given a scenario, apply cybersecurity solutions to the cloud - Given a scenario, implement secure host settings - Given a scenario, implement authentication and authorization solutions - Given a scenario, implement identity and account management controls |
| Architecture and Design | 21% | - Explain the importance of physical security controls - Given a scenario, implement cybersecurity resilience - Summarize virtualization and cloud security concepts - Explain the security implications of embedded and specialized systems - Summarize basics of cryptographic concepts - Explain secure application development, deployment, and automation concepts - Explain the importance of security concepts in an enterprise environment - Summarize authentication and authorization design concepts |
| Governance, Risk, and Compliance | 14% | - Explain risk management processes and concepts - Explain privacy and sensitive data concepts in relation to security - Compare and contrast various types of security controls - Summarize regulations, standards, and frameworks that impact organizations - Given a scenario, follow organizational security policies and procedures |
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NEW QUESTION # 70
A global security operations center (SOC) wants to adapt and leverage the strength of AI in order to enhance its security operations.
Which of the following is the best way to enhance the global SOC functions?
Answer: D
Explanation:
Basic Concept: AI can augment SOC operations in various ways, but the most appropriate uses maintain human oversight and leverage AI ' s natural language understanding to reduce cognitive load on analysts.
CompTIA SecAI+ Study Guide identifies alert summarization as a high-value, low-risk AI application for SOC enhancement.
Why D is Correct: AI-powered alert summarization consolidates complex, high-volume security alerts into concise, actionable insights, helping analysts rapidly understand threats without reading extensive raw log data. This is a safe, bounded AI application that enhances analyst efficiency while preserving human decision- making authority, directly addressing the volume and complexity challenges SOCs face.
Why A is Wrong: Generating and executing code directly in production without human review introduces serious risk. AI-generated code may contain errors, security vulnerabilities, or unintended side effects that could disrupt or compromise production systems.
Why B is Wrong: Enabling an AI assistant to act autonomously with no human intervention violates the human-in-the-loop principle. Autonomous AI in a SOC without oversight could incorrectly contain legitimate systems, miss actual threats, or make consequential decisions without accountability.
Why C is Wrong: Deploying open-source models directly in production without proper vetting, security hardening, and compliance review introduces supply chain risk, model reliability concerns, and potential intellectual property issues into sensitive security operations.
NEW QUESTION # 71
SIMULATION
Instructions
Click the (+) to assign each threat category into its appropriate framework.
If at any time you would like to bring back the initial state of the simulation, please click the Reset All button.
An architect is modeling an agentic system to meet security standards.
Answer:
Explanation:
Explanation:
MAESTRO: Overreliance, Insecure plug-in design
OWASP Top 10: Broken access control, Identification and authentication failures OWASP Top 10 LLM: Prompt injection, Model denial of service STRIDE: Elevation of privilege, Repudiation, Supply chain vulnerabilities, Insecure design MAESTRO addresses AI-specific misuse such as excessive trust in outputs (overreliance) and unsafe plug-in design.
OWASP Top 10 maps to classic web threats: broken access control and authentication failures are key risks.
OWASP Top 10 LLM focuses on LLM-related threats like prompt injection and denial of service targeting the model.
STRIDE categories cover privilege escalation, repudiation (denying actions), supply chain risks, and insecure design flaws.
NEW QUESTION # 72
Which of the following are considered threat intelligence sources? (Choose two.)
Answer: D,E
Explanation:
ISACs and OSINT provide structured and open-source threat intelligence feeds.
NEW QUESTION # 73
An organization wants to reduce vulnerabilities after deployment. The organization decides to incorporate an AI-assisted early detection and vulnerability identification process in its development workflow.
Which of the following AI-assisted functions is the best option?
Answer: D
Explanation:
Basic Concept: Reducing post-deployment vulnerabilities requires catching security issues as early as possible in the development workflow. AI-assisted tools that analyze code during development provide the earliest possible intervention point. CompTIA SecAI+ Study Guide covers AI integration in secure development under AI-assisted security.
Why A is Correct: AI-assisted code linting analyzes source code in real time during development to identify security vulnerabilities, insecure coding patterns, policy violations, and quality issues before code is compiled or committed. By catching vulnerabilities at the coding stage - the earliest possible point in the development workflow - AI code linting prevents vulnerable code from progressing to testing, staging, or production, directly reducing post-deployment vulnerabilities at their source.
Why B is Wrong: Incident management handles security events and incidents after they have occurred in production. It is a reactive capability focused on response and recovery rather than early-stage vulnerability identification in the development workflow.
Why C is Wrong: Automated deployment/rollback automates the process of pushing code to production and reverting to previous versions when issues are detected post-deployment. It is a deployment safety mechanism rather than an early detection tool during the development phase.
Why D is Wrong: System auditing reviews and records system activities and configurations for compliance verification. It is primarily a detective and compliance control for systems that are already deployed, not an early development-phase vulnerability identification tool.
NEW QUESTION # 74
An AI security administrator notices that the information referenced by the model is incorrectly formatted and missing values. Which of the following job roles would most likely be responsible for correcting this error?
Answer: B
Explanation:
A data engineer is responsible for preparing, cleaning, and formatting data pipelines. When information is incorrectly formatted or missing values, the data engineer ensures data integrity and quality before it is used by AI models.
NEW QUESTION # 75
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