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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Securing AI Systems | 40% | - Adversarial Defense
|
| Topic 2: AI Governance, Risk, and Compliance | 19% | - Risk and Compliance
|
| Topic 3: Basic AI Concepts Related to Cybersecurity | 17% | - AI Threat Landscape
|
| Topic 4: AI-Assisted Security | 24% | - Operational Use of AI
|
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NEW QUESTION # 51
A disgruntled employee changed the company policies that a chatbot references in order to create confusion and disrupt the business.
Which of the following AI-generated vulnerabilities is the employee exploiting?
Answer: D
Explanation:
Basic Concept: AI systems that rely on knowledge bases, vector databases, or reference documents are vulnerable to attacks that corrupt or manipulate that source data. When an adversary deliberately modifies the data an AI uses, this is a form of data poisoning. CompTIA SecAI+ Study Guide covers data poisoning as a core AI vulnerability.
Why C is Correct: Data poisoning is an attack where an adversary intentionally corrupts or manipulates the data that an AI system uses for training, inference, or reference. In this scenario, the employee modified the company policies document that the chatbot uses as its knowledge base, causing the chatbot to provide incorrect, misleading, or confusing information to users. This is a classic indirect data poisoning attack targeting the AI ' s reference data rather than its model weights.
Why A is Wrong: Data reduction refers to techniques that decrease the volume or dimensionality of data for processing efficiency. It is a data engineering concept, not an attack vector or vulnerability classification.
Why B is Wrong: Data masking replaces sensitive data values with anonymized equivalents to protect privacy. It is a data protection control used legitimately, not an attack that an employee would exploit to cause disruption.
Why D is Wrong: Data leaking involves unauthorized disclosure of sensitive information from an AI system or its associated data stores. The employee ' s action of manipulating data is an integrity attack, not a confidentiality violation involving leakage of data to unauthorized parties.
NEW QUESTION # 52
A security analyst finds that the AI system is under a denial-of-wallet attack.
Which of the following should the analyst enforce to protect the company? (Choose two.)
Answer: B,F
NEW QUESTION # 53
A security operations center (SOC) has a very high volume of logs and alerts. The manager proposes the implementation of machine learning (ML) system to help with triage. Which of the following tasks is most suitable?
Answer: B
Explanation:
Machine learning is best suited for analyzing large volumes of security data and distinguishing between true threats and false positives. By identifying and classifying alerts, the ML system helps the SOC prioritize incidents and reduce analyst workload.
NEW QUESTION # 54
During the selection of a machine learning (ML)-based threat classification model, a cybersecurity administrator verifies that label distribution is highly unbalanced. Which of the following processing techniques should the engineer use to balance the model?
Answer: C
Explanation:
When label distribution is highly unbalanced, data augmentation generates additional synthetic samples for the underrepresented classes. This balances the dataset, improving the ML model's ability to classify threats accurately across all categories.
NEW QUESTION # 55
A security consultant needs to detect attacks across a large language model (LLM) firewall.
Which of the following techniques should the consultant use?
Answer: C
Explanation:
Basic Concept: LLM firewalls inspect prompts and responses to identify malicious content, policy violations, and attack attempts. To detect known attack patterns, these systems apply inspection techniques that compare content against established threat indicators. CompTIA SecAI+ Study Guide covers LLM security monitoring and detection techniques.
Why A is Correct: Signature matching compares incoming prompts and outgoing responses against a library of known attack signatures, including common prompt injection patterns, jailbreaking attempts, data exfiltration queries, and known malicious payload strings. When content matches a known attack signature, the LLM firewall can block or flag it. Signature matching is an efficient, proven detection technique for identifying known attack patterns traversing an LLM firewall.
Why B is Wrong: Distributed denial-of-service is itself a type of attack, not a detection technique. DDoS floods systems with traffic to cause service unavailability and has no role in detecting attacks through an LLM firewall.
Why C is Wrong: Translation analysis involves converting content between languages or formats. While it might be used to detect obfuscated attacks in different encodings, it is not a standard detection technique for identifying attacks crossing an LLM firewall.
Why D is Wrong: Vulnerability enumeration systematically identifies and catalogs vulnerabilities in systems or applications during security assessments. It is an assessment activity used to discover weaknesses, not a real-time detection technique for attacks traversing an LLM firewall.
NEW QUESTION # 56
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