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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Securing AI Systems | 40% | - Secure AI development and operations
|
| Topic 2: AI-assisted Security | 24% | - AI in security strategy and operations
|
| Topic 3: AI Governance, Risk and Compliance | 19% | - Governance frameworks and policies
|
| Topic 4: Basic AI Concepts Related to Cybersecurity | 17% | - Core AI principles and terminology
|
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NEW QUESTION # 83
A user interface engineer adds new graphics to the latest release of an AI-integrated application. During the update, the engineer accidentally causes the model to retrain on unverified data. After the update, the model begins to return many errors.
Which of the following is the best way to mitigate future errors?
Answer: C
Explanation:
Basic Concept: When a non-ML engineer can accidentally trigger model retraining during a UI update, this indicates a lack of proper lifecycle management and change controls around the AI model. Uncontrolled retraining on unverified data is a critical vulnerability in the development and deployment process. CompTIA SecAI+ Study Guide identifies the Model Development Life Cycle as the framework for preventing such issues.
Why C is Correct: Implementing a Model Development Life Cycle (MDLC) establishes formal, controlled processes for every stage of model development and updates including data validation requirements before training, change management gates, testing and validation stages, and separation of duties between UI development and model training activities. An MDLC would have prevented the accidental retraining by requiring explicit, controlled authorization before any model training occurs.
Why A is Wrong: A WAF filters HTTP traffic at the application boundary. It does not govern internal development processes or control when and how model retraining occurs within the AI development pipeline.
Why B is Wrong: Role-based access control can restrict who has permission to trigger model retraining, which would help prevent this specific incident. However, it is one component of a broader MDLC governance framework and does not address data validation, testing stages, or the complete change management process.
Why D is Wrong: A GAN is a model architecture for generating synthetic data. It is a training technique unrelated to lifecycle governance or preventing accidental retraining from unverified data during unrelated application updates.
NEW QUESTION # 84
Which of the following describes the number of training cycles used in an AI model for threat detection?
Answer: A
Explanation:
Basic Concept: Training an AI model involves repeatedly exposing it to training data so it can learn optimal parameters. The terminology for training cycles is fundamental to understanding AI model training processes.
CompTIA SecAI+ Study Guide covers core AI training concepts under basic AI concepts.
Why D is Correct: An epoch refers to one complete pass through the entire training dataset. When a model trains for multiple epochs, it sees each training example multiple times, allowing it to refine its parameters progressively. The number of training epochs is a key hyperparameter that directly affects model performance
- too few and the model underfits; too many and it may overfit. For a threat detection model, specifying epochs controls how thoroughly the model has learned from the training data.
Why A is Wrong: k-means clustering is an unsupervised machine learning algorithm that groups data points into k clusters based on feature similarity. It is a data clustering algorithm, not a term describing training cycles or iterations.
Why B is Wrong: Tokens are the discrete units that LLMs use to process text inputs and outputs. Token count measures text processing volume and LLM utilization, not the number of times a model has processed its training dataset.
Why C is Wrong: Temperature is an inference parameter that controls the randomness or creativity of an LLM ' s output generation. Higher temperature produces more varied outputs; lower temperature produces more deterministic responses. It is not related to training cycles or iterations.
NEW QUESTION # 85
Which are indicators of lateral movement? (Choose two.)
Answer: A,B
Explanation:
Lateral movement often involves internal SMB attacks and credential reuse.
NEW QUESTION # 86
An AI security team must assess the probability of an attack on its new system and the impact associated with such an attack.
Which of the following threat-modeling resources best addresses the threat landscape for machine learning (ML)?
Answer: A
Explanation:
Basic Concept: Assessing attack probability and impact for ML systems requires a resource specifically built to catalog real-world adversarial attacks against AI and ML systems, including documented techniques with associated impact information. CompTIA SecAI+ Exam Objectives identify MITRE ATLAS as the authoritative ML threat landscape resource.
Why B is Correct: MITRE ATLAS is specifically designed as a comprehensive knowledge base of adversarial tactics, techniques, and case studies targeting AI and ML systems. It catalogs real-world attacks with associated probability factors derived from actual incidents and provides impact assessments for various attack types including data poisoning, model evasion, model extraction, and inference attacks. This directly enables the probability and impact assessment the team requires.
Why A is Wrong: The CVE AI working group focuses on identifying and cataloging specific vulnerability instances in AI software components. While useful for vulnerability management, it does not provide the comprehensive threat landscape coverage with probability and impact assessments for ML-specific attack tactics that ATLAS provides.
Why C is Wrong: The MIT risk repository is an academic resource cataloging general AI-related risks. It is research-oriented and does not provide the practitioner-focused, operational attack taxonomy and case study library that MITRE ATLAS offers for ML threat modeling.
Why D is Wrong: OWASP provides application security guidance including the OWASP LLM Top 10. While valuable for LLM-specific risks, OWASP does not provide the comprehensive ML threat landscape coverage or the probability and impact data that MITRE ATLAS offers for assessing the full spectrum of ML attack scenarios.
NEW QUESTION # 87
An organization deploys a browser-based AI plug-in to detect malicious websites and phishing links in corporate email.
Which of the following techniques is used in this AI plug-in?
Answer: C
Explanation:
Basic Concept: AI-based security tools for detecting malicious websites and phishing links operate by analyzing URLs, page content, and link characteristics against known malicious patterns and behavioral signatures. CompTIA SecAI+ Study Guide covers pattern recognition and signature matching as fundamental AI-assisted threat detection techniques.
Why B is Correct: Pattern recognition and signature matching are the core techniques used in malicious website and phishing link detection. The AI plug-in uses pattern recognition to identify characteristics of phishing pages such as login form structures mimicking legitimate sites, suspicious domain patterns, and redirect behaviors. Signature matching compares URLs and page content against databases of known malicious sites and phishing infrastructure. Together these techniques enable accurate detection of threats in email links before users click them.
Why A is Wrong: Code quality testing analyzes source code for bugs, vulnerabilities, and adherence to coding standards during software development. It has no application for detecting malicious websites or phishing links in real-time email scanning.
Why C is Wrong: Automated penetration testing proactively exploits vulnerabilities to assess security posture.
It is an offensive security assessment technique, not a real-time threat detection technique for identifying malicious links in email.
Why D is Wrong: Automated incident response executes predefined response actions when security incidents are detected, such as isolating endpoints or blocking users. It operates after threats are detected, not during the detection phase that identifies malicious websites and links.
NEW QUESTION # 88
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