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| Section | Weight | Objectives |
|---|---|---|
| Implementation | 25% | - Given a scenario, implement identity and account management controls - Given a scenario, implement public key infrastructure (PKI) - Given a scenario, implement secure mobile device policies - Given a scenario, implement secure host settings - Given a scenario, apply cybersecurity solutions to the cloud - Given a scenario, implement secure network architecture concepts - Given a scenario, implement secure systems design - Given a scenario, implement authentication and authorization solutions |
| Governance, Risk, and Compliance | 14% | - Compare and contrast various types of security controls - Explain privacy and sensitive data concepts in relation to security - Explain risk management processes and concepts - Given a scenario, follow organizational security policies and procedures - Summarize regulations, standards, and frameworks that impact organizations |
| Attacks, Threats, and Vulnerabilities | 24% | - Given a scenario, analyze potential indicators associated with application attacks - Explain penetration testing concepts - 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 - Explain threat actor types and attributes - Compare and contrast types of social engineering attacks |
| Operations and Incident Response | 16% | - Summarize the importance of policies, processes, and procedures for incident response - Given a scenario, use data sources to support an investigation - Explain key aspects of digital forensics - Given a scenario, use appropriate tool to assess organizational security - Given a scenario, apply mitigation techniques or controls to secure an environment |
| Architecture and Design | 21% | - Given a scenario, implement cybersecurity resilience - Explain the importance of security concepts in an enterprise environment - Explain secure application development, deployment, and automation concepts - Explain the importance of physical security controls - Explain the security implications of embedded and specialized systems - Summarize basics of cryptographic concepts - Summarize authentication and authorization design concepts - Summarize virtualization and cloud security concepts |
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NEW QUESTION # 78
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: B
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 # 79
A team of data scientists is ready to release a model for enterprise use. The team wants to protect the model from unintentional changes or tampering. Which of the following is the most appropriate action?
Answer: D
Explanation:
Protecting the model from tampering requires controlled and auditable access. By integrating the model with an API secured by IAM roles, only authenticated and authorized users or systems can interact with it, ensuring integrity and preventing unauthorized changes.
NEW QUESTION # 80
Instructions: Use the drop-down menus to define two appropriate security controls for each component of the AI system. Each control may be used only once.
An engineer is deploying a new AI system and wants to integrate it into the core system through an API.
Answer:
Explanation:
Explanation:
Basic Concept: This is a Performance-Based Question (PBQ) - a HOTSPOT/simulation item requiring interactive selection in the actual exam. It tests the candidate ' s ability to map appropriate security controls to AI system components such as API gateway, model endpoint, data layer, and authentication layer.
Key Concept - Appropriate Controls by Component: For an API gateway connecting an AI system, typical controls include API key authentication, rate limiting, TLS encryption, and input validation. For the model endpoint, controls include IAM role-based access, audit logging, and guardrails. For data access components, encryption at rest and data masking are appropriate. For the authentication layer, MFA and expiring session tokens are relevant.
Why This Matters: The CompTIA SecAI+ Study Guide emphasizes defense-in-depth for AI system integration, ensuring each architectural layer has dedicated, appropriate security controls. The principle of least privilege should guide access control assignments at each component, while availability controls such as rate limiting protect against abuse.
Reference: CompTIA SecAI+ Exam Objectives Domain 2 (Securing AI Systems) covers AI system component security controls. Candidates should study the mapping of controls to infrastructure components including API gateways, model serving endpoints, data stores, and identity management layers. In the live exam, select the most specific and directly relevant control for each component based on the component ' s function and risk profile.
NEW QUESTION # 81
Which of the following responsible AI standards refers to a principle that clearly states the reasons behind the decisions for a particular conclusion?
Answer: B
Explanation:
Explainability is the responsible AI principle that ensures AI systems can provide clear reasoning for their decisions, allowing users to understand how and why a particular conclusion was reached.
NEW QUESTION # 82
An internal user enters a client credit card number into an internal generative machine learning (ML) model:
#User prompt: Customer Jane Doe has a new credit card that she wants to add to her account. The number is
5555-5555-5555-5555
Which of the following is the most effective way to prevent prompt injection attacks against a large language model (LLM)?
Answer: A
Explanation:
Basic Concept: Prompt injection occurs when malicious content embedded in user input manipulates an LLM
' s behavior, causing it to leak sensitive data, bypass restrictions, or execute unintended actions. Preventing such attacks requires mechanisms that inspect and filter content at the prompt level. CompTIA SecAI+ covers LLM-specific security controls extensively.
Why A is Correct: Guardrails are purpose-built controls that inspect, filter, and constrain both input prompts and output responses in LLM systems. They can detect sensitive data patterns such as credit card numbers, block prompt injection payloads, enforce content policies, and prevent the model from processing or outputting restricted information. Guardrails are the primary LLM-native defense against prompt injection as cited in the CompTIA SecAI+ Study Guide.
Why B is Wrong: Antivirus software detects known malware signatures in files and executables. It does not inspect or understand the semantic content of LLM prompts and cannot detect or block prompt injection attacks.
Why C is Wrong: A WAF operates at the HTTP layer inspecting web requests and responses against rule sets.
While it can block some patterns, it lacks the contextual intelligence to understand LLM prompt semantics and cannot prevent sophisticated injection attacks.
Why D is Wrong: Role-based access control manages who can access which resources. It controls authorization but does not inspect the content of prompts to prevent injection attacks once a user has legitimate access.
NEW QUESTION # 83
......
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