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| Section | Weight | Objectives |
|---|---|---|
| AI-assisted Security | 24% | - Security automation and orchestration
|
| Basic AI Concepts Related to Cybersecurity | 17% | - AI-driven threats and risks
|
| AI Governance, Risk and Compliance | 19% | - Compliance and legal requirements
|
| Securing AI Systems | 40% | - Defending against AI-specific attacks
|
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NEW QUESTION # 53
Which of the following job roles in an organizational governance structure develops a model from business use cases?
Answer: D
Explanation:
A data scientist develops models from business use cases by translating organizational needs into machine learning solutions. They prepare data, select algorithms, and build models that align with the use cases.
NEW QUESTION # 54
Customer feedback for an AI chatbot has a high-rate of non-answers, which is causing higher central processing unit (CPU) utilization.
Which of the following should be implemented?
Answer: D
Explanation:
Basic Concept: AI chatbots that generate non-answers - responses that do not actually address user questions
- consume CPU resources for processing without delivering value. This can indicate the model is attempting to generate responses for queries outside its knowledge domain or confidence threshold. CompTIA SecAI+ Study Guide covers AI performance optimization and response quality management.
Why B is Correct: Implementing a response confidence level threshold allows the chatbot to recognize when it lacks sufficient confidence to provide a meaningful answer and respond accordingly, either with a helpful redirect or a clear indication that it cannot answer the query. This reduces the costly processing cycles spent generating poor-quality non-answers, lowers CPU utilization from failed response generation, and improves customer experience by setting appropriate expectations rather than returning unhelpful responses.
Why A is Wrong: Guardrails filter content for safety and policy compliance. They prevent harmful or out-of- policy responses but do not address the underlying issue of the model generating low-confidence non-answers to legitimate customer queries.
Why C is Wrong: Prompt logging records user inputs for analysis and auditing. While useful for identifying what types of questions cause non-answers, logging alone does not solve the problem or reduce CPU utilization from failed response generation.
Why D is Wrong: Cost monitoring tracks AI system expenditure. It can identify that costs are high due to excessive CPU usage but does not implement a solution to reduce the non-answer rate or improve response generation efficiency.
NEW QUESTION # 55
A SOC analyst identifies that a user extracted the full system prompt from the company ' s chatbot by prompting it to repeat the last query and provide the entire conversation context. Which of the following mitigations reduces the risk to the AI system?
Answer: D
Explanation:
Basic Concept: System prompt extraction is an attack where users manipulate an LLM into revealing its confidential system instructions. This violates the confidentiality of proprietary prompts and can expose security controls and business logic to adversaries. CompTIA SecAI+ Study Guide identifies guardrails as the primary control for preventing system prompt disclosure.
Why C is Correct: Enhancing model guardrails can specifically include instructions and filters that prevent the model from revealing its system prompt contents, regardless of how users attempt to extract them. Guardrails can detect and block attempts to retrieve conversation history, repeat system-level instructions, or disclose confidential operational context. This directly addresses the demonstrated attack where the user prompted the chatbot to reveal its entire context including the system prompt.
Why A is Wrong: Restricting the LLM ' s access to internal services limits what external resources the model can query. While this reduces the potential impact of system compromise, it does not prevent the model from disclosing its own system prompt in response to carefully crafted user queries.
Why B is Wrong: Data version control tracks changes to datasets and documents over time. It is a data management tool that does not inspect or control what the model discloses in its conversational responses to users.
Why D is Wrong: Segregating and identifying external content is relevant for preventing prompt injection from external data sources. It does not directly prevent a user from successfully prompting the model to reveal its own internal system instructions.
NEW QUESTION # 56
A security administrator must provide access controls for AI systems to list tables.
Which of the following should the administrator implement?
Answer: A
Explanation:
Basic Concept: AI systems interact with different resource layers including models, data stores, and infrastructure. Controlling what data an AI system can access requires implementing access controls at the data layer. CompTIA SecAI+ Study Guide differentiates between model access, data access, and network access controls for AI systems.
Why D is Correct: Data access controls govern what data resources an AI system can interact with, including which databases, tables, and records it can read or modify. To control an AI system ' s ability to list database tables, the administrator must implement data access controls that define precisely which tables the AI can enumerate and query, following the principle of least privilege for data interactions.
Why A is Wrong: Agentic AI access refers to permissions granted to autonomous AI agents to perform actions and use tools. It is a broader concept about what an AI agent can do operationally rather than a specific data-layer access control mechanism.
Why B is Wrong: A Network Access Control List controls network traffic at the IP and port level, determining which hosts can communicate with which network resources. It operates at the network layer and cannot enforce fine-grained control over which database tables an AI system is allowed to list.
Why C is Wrong: Model access controls govern who and what can interact with the AI model itself - who can query it, update it, or access its parameters. This is distinct from data access, which controls what the model can read from data stores during operation.
NEW QUESTION # 57
A security operations center (SOC) has a very high volume of logs and alerts. The manager proposes the implementation of a machine learning (ML) system to help with triage.
Which of the following tasks is most suitable?
Answer: B
Explanation:
Basic Concept: ML models excel at classification tasks, learning to assign incoming data points to predefined categories based on patterns in training data. In a SOC context, alert classification is the highest-value triage function ML can perform. CompTIA SecAI+ Exam Objectives address AI-assisted security operations under Domain 3.
Why C is Correct: ML-based alert classification automatically analyzes characteristics of each alert and assigns it to a severity category such as critical, high, medium, or low, or to a threat type such as malware or intrusion attempt. This dramatically reduces analyst workload and speeds triage by prioritizing which alerts demand immediate human attention, directly solving the high-volume problem.
Why A is Wrong: Applying filters on specific alerts is a rule-based operation achievable without ML using simple log management tools. It requires no learning capability and does not adapt to new or evolving threats.
Why B is Wrong: Automatically patching systems is a remediation action requiring validated, controlled processes. Having an ML system autonomously patch production systems without human oversight poses unacceptable operational and security risk.
Why D is Wrong: Summarizing alert content is a useful generative AI function but does not provide prioritization value for triage. Classification tells analysts what to act on first; summarization only rephrases existing information.
NEW QUESTION # 58
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