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| Section | Weight | Objectives |
|---|---|---|
| Operations and Incident Response | 16% | - 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 - Given a scenario, use appropriate tool to assess organizational security - Given a scenario, use data sources to support an investigation |
| 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 - Given a scenario, follow organizational security policies and procedures - Summarize regulations, standards, and frameworks that impact organizations |
| Implementation | 25% | - Given a scenario, implement secure host settings - Given a scenario, implement secure mobile device policies - Given a scenario, implement secure network architecture concepts - Given a scenario, implement secure systems design - Given a scenario, implement authentication and authorization solutions - 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) |
| Attacks, Threats, and Vulnerabilities | 24% | - Compare and contrast types of social engineering attacks - Explain threat actor types and attributes - Given a scenario, analyze potential indicators associated with network attacks - Given a scenario, analyze potential indicators to determine the type of attack - Explain vulnerability scanning concepts - Given a scenario, analyze potential indicators associated with application attacks - Explain penetration testing concepts |
| Architecture and Design | 21% | - Summarize virtualization and cloud security concepts - Summarize authentication and authorization design concepts - Explain secure application development, deployment, and automation concepts - Given a scenario, implement cybersecurity resilience - Explain the importance of physical security controls - Summarize basics of cryptographic concepts - Explain the security implications of embedded and specialized systems - Explain the importance of security concepts in an enterprise environment |
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NEW QUESTION # 51
Which of the following attacks would be the best to automate with AI during dynamic application software testing (DAST)?
Answer: C
Explanation:
Basic Concept: Dynamic Application Security Testing (DAST) tests running applications by sending various inputs to discover vulnerabilities. AI can significantly enhance DAST by intelligently generating diverse, targeted test payloads that traditional tools might miss. CompTIA SecAI+ covers AI augmentation of security testing methodologies.
Why C is Correct: Payload creation is highly suitable for AI automation during DAST. AI can generate diverse, contextually appropriate attack payloads such as SQL injection strings, XSS vectors, command injection attempts, and format string exploits tailored to the specific application ' s behavior observed during testing. AI can learn from the application ' s responses to previous payloads and generate increasingly targeted inputs, discovering vulnerabilities more efficiently than static payload databases.
Why A is Wrong: DDoS attacks are volume-based attacks designed to overwhelm network or application infrastructure. Automating DDoS during DAST is inappropriate as it would disrupt service availability rather than discover application security vulnerabilities, and it is harmful to legitimate operations.
Why B is Wrong: Data poisoning is an attack targeting AI/ML model training data integrity. It is relevant to securing AI systems but is not a DAST technique for testing web or software application security vulnerabilities during dynamic testing.
Why D is Wrong: Threat modeling is a structured analysis process performed before development or testing to identify potential threats and design appropriate countermeasures. It is a planning activity, not an attack technique that can be automated during dynamic application security testing.
NEW QUESTION # 52
A security administrator needs to improve an AI model. During an initial investigation, the administrator notices that two successive login features are recorded every day, and then a successful login occurs after a specific time interval. All the successful login attempts have been during office hours.
Which of the following techniques should the administrator use to improve the AI model's security?
Answer: B
Explanation:
The administrator is analyzing repeated login behaviors and time-based patterns that precede successful access. Pattern recognition allows the AI model to detect these behavioral trends, improving its ability to identify anomalies or potential attacks while aligning with normal office-hour login behavior.
NEW QUESTION # 53
A company launches an AI application to monitor cloud misconfiguration and compliance. The AI application is shutting down development servers and opening ports during a client demonstration. Which of the following actions should the company take to return to normal operations and prevent future issues?
Answer: B
Explanation:
Option D is correct because the AI application is taking high-impact remediation actions without adequate human authorization. Human-in-the-loop control requires a qualified person to review and approve consequential actions, such as stopping servers or changing firewall exposure, before execution. The system may still detect misconfigurations, rank risks, and recommend fixes, but it should not autonomously disrupt development or alter network access during a demonstration. Option A restores service temporarily but leaves the unsafe decision path unchanged. Option B removes useful monitoring and does not correct the excessive automation. Option C might close improperly opened ports, yet it addresses only one symptom and does not prevent the AI from repeating other damaging actions. The stronger design is to roll back the unauthorized changes, restrict the agent's permissions, require approval for disruptive operations, and maintain an auditable record of recommendations and approvals. The NIST AI Risk Management Framework calls for appropriate human-oversight processes to be defined, assessed, and documented, supporting this governance pattern.
NEW QUESTION # 54
A company is adopting AI and wants to create policies and procedures that include a structure for evaluating, publishing, and approving patterns for AI usage.
Which of the following should the company establish to meet this goal?
Answer: A
Explanation:
Basic Concept: Successful AI adoption at an organizational level requires a centralized governance body that standardizes AI practices, promotes best practices, and ensures consistent, safe, and effective AI deployment across the organization. CompTIA SecAI+ Study Guide covers AI organizational governance structures under Domain 4.
Why A is Correct: An AI Center of Excellence (CoE) is an organizational unit specifically designed to govern, standardize, and advance AI adoption. It develops and publishes policies, creates approved patterns for AI usage, evaluates new AI use cases, provides expert guidance, and maintains governance oversight. The CoE exactly matches the described need for a structure to evaluate, publish, and approve AI usage patterns across the organization.
Why B is Wrong: An AI legal affairs office focuses on legal compliance, intellectual property, and regulatory matters related to AI. While important for legal risk management, it does not fulfill the broader governance mandate of establishing and approving AI usage patterns and best practices across the organization.
Why C is Wrong: An AI audit department conducts post-implementation reviews and compliance assessments of existing AI systems. It is a retrospective and oversight function rather than a proactive body for developing and approving AI usage patterns and policies.
Why D is Wrong: An AI data science division is a technical team focused on building AI models and solutions. It is a development function rather than a governance structure designed to create policies, evaluate AI patterns, and provide cross-organizational oversight of AI adoption.
NEW QUESTION # 55
A security operations center (SOC) analyst needs to automate multiple security tasks by breaking them down into smaller parts. Which of the following AI tools is the best for this task?
Answer: A
Explanation:
Agentic AI is designed to autonomously break down complex tasks into smaller steps and execute them in sequence. This makes it the best tool for automating multiple security tasks in a SOC environment.
NEW QUESTION # 56
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