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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Securing AI Systems | 40% | - Security controls for AI systems
|
| Topic 2: Basic AI Concepts Related to Cybersecurity | 17% | - Core AI principles and terminology
|
| Topic 3: AI-assisted Security | 24% | - AI for threat detection and response
|
| Topic 4: AI Governance, Risk and Compliance | 19% | - Risk management for AI
|
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NEW QUESTION # 133
An administrator must conduct generative AI cost monitoring for use in the healthcare industry.
Which of the following criteria is the best way to calculate this cost?
Answer: B
Explanation:
Basic Concept: Generative AI systems in healthcare settings incur costs from multiple operational activities.
Understanding the cost drivers specific to generative AI helps administrators implementaccurate cost monitoring and controls. CompTIA SecAI+ Study Guide covers AI cost management under securing AI systems.
Why C is Correct: Storage retrieval and prompt processing are the two primary cost drivers for generative AI systems in healthcare. Storage retrieval refers to the cost of querying vector databases or document stores in RAG-based AI systems to fetch relevant patient records, clinical guidelines, or historical data for context.
Prompt processing encompasses the token-based cost of the LLM processing the combined retrieved content and user query to generate a response. Together these two activities represent the billable units that drive generative AI costs in healthcare RAG deployments, making them the most accurate basis for cost calculation and monitoring.
Why A is Wrong: Connection access and exchange gateway costs relate to network infrastructure and API gateway usage fees. While there may be minor costs associated with API calls, these are not the primary cost drivers for generative AI systems where the dominant expenses are computational token processing and data retrieval operations.
Why B is Wrong: Encryption and decryption processing costs relate to cryptographic operations for data security. While encryption is important for healthcare data protection under HIPAA, cryptographic processing overhead is minimal compared to the substantial token-based LLM processing and storage retrieval costs that dominate generative AI operational expenses.
Why D is Wrong: Catalog servicing and exchange processing are terms associated with data catalog management and data exchange infrastructure. These are not recognized primary cost components of generative AI systems in healthcare, where storage retrieval and token-based prompt processing are the established cost measurement criteria.
NEW QUESTION # 134
An AI security architect needs to conduct a security review of a new AI chatbot. Which of the following resources would the architect most likely rely on to perform a threat assessment and ensure comprehensive coverage during the review?
Answer: D
Explanation:
The OWASP Top 10 for Large Language Model Applications is the most directly applicable resource because the system under review is an AI chatbot based on LLM technology. CompTIA SecAI+ Objective 2.1 explicitly identifies the OWASP Top 10, including the LLM Top 10, as an AI threat-modeling resource. It addresses security risks specifically associated with LLM applications, including prompt injection, sensitive information disclosure, insecure output handling, excessive agency, and other AI-specific application threats.
ISO 27001 provides a broader information security management framework and is valuable for organizational security governance, but it is not specifically designed to enumerate LLM attack vectors. The EU AI Act primarily addresses regulatory obligations, risk classifications, and governance requirements rather than serving as a technical LLM threat-assessment checklist. Option A is also not the appropriate LLM-specific resource. For a security architect who needs systematic technical coverage of threats affecting an AI chatbot, the OWASP LLM Top 10 provides the most targeted framework among the listed options.
NEW QUESTION # 135
A security administrator must provide access controls for AI systems to list tables. Which of the following should the administrator implement?
Answer: D
Explanation:
Since the requirement is to control which users or systems can list tables, the proper control lies at the data access level. Implementing data access controls ensures only authorized entities can view or query the underlying tables used by the AI system.
NEW QUESTION # 136
Users report that the output of a generative AI application seems unrelated to the prompts and contains offensive content. A security team investigates and determines that there was an on-path attack.
Which of the following is the most likely attack method?
Answer: D
Explanation:
Basic Concept: An on-path (formerly man-in-the-middle) attack intercepts communication between two parties, allowing the attacker to read, modify, or inject content. In the context of a generative AI application, an on-path attack on the session between user and AI service can manipulate prompts being sent to the model or responses being returned to users. CompTIA SecAI+ covers AI-specific attack vectors under securing AI systems.
Why B is Correct: Session hijacking involves an attacker taking control of an active user session by capturing or forging session tokens. In this attack, the attacker intercepts the communication channel between users and the AI application, allowing them to modify prompts sent to the model or replace legitimate model responses with offensive content. This explains why outputs seem unrelated to prompts and contain offensive material.
Why A is Wrong: Application server hijacking involves gaining unauthorized control of the server hosting the application. While severe, this would typically manifest as complete service disruption or data exfiltration rather than targeted modification of individual user session content.
Why C is Wrong: Domain hijacking involves unauthorized transfer of a domain name registration, redirecting all users to a different IP address. This would affect all users simultaneously and typically redirect to a completely different site rather than manipulating individual AI responses.
Why D is Wrong: Model hijacking refers to attacks that steal or replicate an AI model, not to intercepting and modifying the communication between users and an existing model during active sessions.
NEW QUESTION # 137
A security administrator needs to improve an AI model. During an initial investigation, the administrator notices that two successive login failures 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: D
Explanation:
Basic Concept: Pattern recognition is an AI technique that enables a system to identify recurring sequences or structures within data. In cybersecurity, detecting behavioral patterns such as consistent pre-login failure sequences followed by successful access is critical for threat detection. CompTIA SecAI+ Exam Objectives cover this under AI-assisted security.
Why B is Correct: The scenario describes a highly regular, repeating behavioral pattern - two failures followed by success at a specific time interval, consistently during office hours. Pattern recognition enables the AI model to learn this sequence and flag it as indicative of credential stuffing or an automated brute-force attack with timing controls. ML-driven pattern recognition is specifically designed for such behavioral anomaly detection.
Why A is Wrong: Access management controls who can log in and under what conditions. It enforces authorization policies but does not analyze or detect suspicious behavioral sequences in authentication logs.
Why C is Wrong: Signature matching compares known attack signatures against observed data. The described pattern is behavioral and time-based rather than a known malware or exploit signature, making this technique unsuitable.
Why D is Wrong: Vulnerability analysis identifies weaknesses in systems and code. It does not analyze authentication log sequences or detect behavioral patterns in user activity data.
NEW QUESTION # 138
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