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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implementation | 25% | - Given a scenario, implement authentication and authorization solutions - Given a scenario, implement secure host settings - Given a scenario, implement identity and account management controls - Given a scenario, implement secure network architecture concepts - Given a scenario, apply cybersecurity solutions to the cloud - Given a scenario, implement secure systems design - Given a scenario, implement secure mobile device policies - Given a scenario, implement public key infrastructure (PKI) |
| Topic 2: Architecture and Design | 21% | - Explain the importance of physical security controls - Summarize basics of cryptographic concepts - Given a scenario, implement cybersecurity resilience - Summarize virtualization and cloud security concepts - Summarize authentication and authorization design concepts - Explain the importance of security concepts in an enterprise environment - Explain the security implications of embedded and specialized systems - Explain secure application development, deployment, and automation concepts |
| Topic 3: Attacks, Threats, and Vulnerabilities | 24% | - Given a scenario, analyze potential indicators to determine the type of attack - 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 - Explain vulnerability scanning concepts - Explain threat actor types and attributes - Explain penetration testing concepts |
| Topic 4: Operations and Incident Response | 16% | - Given a scenario, use appropriate tool to assess organizational security - Summarize the importance of policies, processes, and procedures for incident response - Explain key aspects of digital forensics - Given a scenario, use data sources to support an investigation - Given a scenario, apply mitigation techniques or controls to secure an environment |
| Topic 5: Governance, Risk, and Compliance | 14% | - Given a scenario, follow organizational security policies and procedures - Explain privacy and sensitive data concepts in relation to security - Summarize regulations, standards, and frameworks that impact organizations - Explain risk management processes and concepts - Compare and contrast various types of security controls |
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NEW QUESTION # 104
Hotspot Question
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.
If at any time you would like to bring back the initial state of the simulation please click the Reset All button.
An engineer is deploying a new AI system and wants to integrate it into the core system through an API.
Answer:
Explanation:
Explanation:
Cloud control plane: IAM policies, Resource policies
Prompt firewall: Injection policies, Output monitoring
WAF: Connection rate limits, Input token validation
Front-end API + Model + Vector database: Guardrails, Input quota
API gateway: Load balancing, Authentication token validation
Cloud control plane relies on IAM and resource policies to enforce centralized identity and access management as well as usage restrictions.
Prompt firewall protects against malicious input via injection policies and ensures outputs are monitored for compliance and safety.
WAF controls connection rate to mitigate DoS and validates input tokens to stop unauthorized access attempts.
Front-end API, Model, and Vector database share guardrails to restrict unsafe behaviors and input quotas to prevent overuse, making them consistent and efficient security points.
API gateway enforces load balancing for availability and validates authentication tokens at the entry point, providing secure and scalable access.
NEW QUESTION # 105
Which of the following job roles in an organizational governance structure develops a model from business use cases?
Answer: D
Explanation:
Basic Concept: In AI governance, each role holds distinct responsibilities. Understanding these roles is core to CompTIA SecAI+ Domain 4 (AI Governance, Risk, and Compliance).
Why D is Correct: The Data Scientist is responsible for translating business use cases into working AI/ML models. They analyze business requirements, identify the appropriate machine learning approach, and develop models that fulfill specific business objectives. According to the CompTIA SecAI+ Study Guide, data scientists bridge raw data and actionable AI solutions by building and validating models derived from business-driven needs.
Why A is Wrong: A Platform Architect designs and manages the infrastructure and technical platforms hosting AI systems. Their focus is architectural design of the environment, not model development from business use cases.
Why B is Wrong: An AI Risk Analyst identifies, evaluates, and mitigates risks associated with AI adoption.
Their role is governance and risk-oriented, not model creation.
Why C is Wrong: An MLOps Engineer operationalizes, deploys, monitors, and maintains AI models in production. They take models already built by data scientists and ensure reliable operation at scale, not develop them from business use cases.
NEW QUESTION # 106
A security consultant needs to detect attacks across a large language model (LLM) firewall.
Which of the following techniques should the consultant use?
Answer: D
Explanation:
Signature matching allows the detection of known malicious patterns, inputs, or behaviors targeting an LLM firewall. It is an effective technique for identifying and blocking prompt injection or other recognized attack methods.
NEW QUESTION # 107
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: D
NEW QUESTION # 108
Which of the following risks most often occurs when developing an internal chatbot?
Answer: D
Explanation:
Data leakage is the most applicable risk because an internal chatbot commonly interacts with organizational information that may include confidential documents, customer information, employee records, credentials, intellectual property, and other sensitive content. CompTIA SecAI+ specifically identifies accidental data leakage as an AI risk and sensitive information disclosure as an attack or failure condition affecting AI systems. Internal chatbots can expose information when retrieval permissions are too broad, conversation context crosses security boundaries, prompts contain confidential material, or model responses reproduce information that the requesting user should not receive. Prompt injection is an important chatbot attack vector, but it describes deliberate manipulation of model instructions rather than the broader organizational risk emphasized here. Model theft concerns unauthorized acquisition or reproduction of a model. Unauthorized access concerns gaining access to resources without proper authorization and is generally addressed through model, data, agent, network, and API access controls. In contrast, information leakage can occur even when legitimate employees are using the chatbot normally. Protecting sensitive data through access controls, minimization, masking, classification, and monitoring is therefore fundamental to internal chatbot security.
NEW QUESTION # 109
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