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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Basic AI Concepts Related to Cybersecurity | 17% | - AI-driven threats and risks
|
| Topic 2: Securing AI Systems | 40% | - Security controls for AI systems
|
| Topic 3: AI-assisted Security | 24% | - AI in security strategy and operations
|
| Topic 4: AI Governance, Risk and Compliance | 19% | - Governance frameworks and policies
|
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NEW QUESTION # 107
A data set containing medical information is put into a machine learning (ML) model that is designed to predict specific illnesses for a population. In the process of verifying the reliability of the system, the compliance officer realizes that the system cannot reliably predict illnesses for certain segments of the population. Which of the following types of risk is most applicable to this case?
Answer: D
Explanation:
The model's inability to reliably predict illnesses for certain population segments indicates bias in the dataset or training process. This leads to unfair or inaccurate outcomes for specific groups, making bias the most applicable risk in this case.
NEW QUESTION # 108
A developer is selecting authentication controls for an AI system.
Which of the following is the best way to prevent threat actor replay attacks?
Answer: C
Explanation:
Basic Concept: A replay attack occurs when an attacker captures a valid authentication token or credential and reuses it to impersonate a legitimate user. Preventing replay attacks requires ensuring that captured credentials cannot be successfully reused after a defined period or after their intended single use. CompTIA SecAI+ Study Guide covers replay attack prevention under AI system authentication.
Why C is Correct: Expiring session tokens have a limited validity window, typically a few minutes to hours.
If an attacker captures a token, they can only use it until it expires. Short expiration times dramatically reduce the window of opportunity for replay attacks. This is the most direct and effective control specifically targeting replay attack prevention, as expired tokens are rejected even if intercepted.
Why A is Wrong: IdP federation enables single sign-on across multiple systems using federated identity providers. While it standardizes authentication, it does not inherently prevent replay attacks on captured tokens unless combined with short token expiration and proper validation.
Why B is Wrong: SSH certificate authentication uses cryptographic certificates for strong authentication.
While more secure than password-based SSH, certificates alone do not prevent replay attacks unless they include timestamps, nonces, or other anti-replay mechanisms that invalidate captured credentials.
Why D is Wrong: IAM access keys are long-lived credentials that provide programmatic access to services.
They are typically static and do not expire automatically, making them vulnerable to replay attacks if intercepted. They are less suitable for replay attack prevention than expiring session tokens.
NEW QUESTION # 109
A security team is using an AI-based tool to try to bypass organizational boundaries. The team uses AI to look at the current state and suggest different attack vectors based on the outcome of the previous ones.
Which of the following techniques is the team most likely using?
Answer: B
Explanation:
Basic Concept: Modern penetration testing increasingly leverages AI to automate the reconnaissance, exploitation, and pivoting process. AI-assisted automated penetration testing can adapt its strategy based on previous results, simulating intelligent adversary behavior more realistically than static scripts. CompTIA SecAI+ covers AI-assisted offensive security techniques.
Why D is Correct: Automated penetration testing uses AI to systematically discover and attempt to exploit vulnerabilities while adapting tactics based on the results of previous attempts. The described behavior - looking at the current state, suggesting attack vectors, and adjusting based on outcomes - precisely describes an adaptive AI-driven penetration testing tool that iteratively explores the attack surface, mimicking how an advanced persistent threat would operate.
Why A is Wrong: Manual signature matching compares network traffic or files against a database of known threat signatures. It is a passive detection technique used by defensive tools like IDS/IPS, not an adaptive offensive technique for bypassing organizational boundaries.
Why B is Wrong: Code quality testing analyzes source code for bugs, vulnerabilities, and adherence to coding standards. It is a development quality assurance activity, not an offensive security technique for testing organizational security boundaries.
Why C is Wrong: Fraud detection uses ML to identify suspicious patterns in transactions or user behavior for defensive purposes. It is a preventive security measure, not an offensive technique for penetration testing.
NEW QUESTION # 110
A data scientist investigates reports that a production machine learning (ML) model no longer performs with accuracy.
The data scientist finds the following pipeline log entries:
Which of the following should the security team do to mitigate future occurrences?
Answer: A
Explanation:
Basic Concept: When unauthorized changes to an ML training pipeline cause model degradation, the root cause is insufficient access control and change management around the pipeline. Preventing future occurrences requires implementing governance controls that ensure all pipeline changes are reviewed and approved before execution. CompTIA SecAI+ Study Guide covers MDLC change management controls.
Why B is Correct: Enabling human review and approval workflows in the repository creates a mandatory gate requiring authorized reviewers to examine and approve any changes to training pipeline code before they can be merged and executed. This prevents unauthorized modifications from reaching the pipeline by enforcing a review process where any suspicious or unauthorized changes will be caught and rejected before they affect model training and performance.
Why A is Wrong: Static code scanning analyzes code for vulnerabilities and coding standard violations.
While it improves code quality and security, it does not prevent unauthorized individuals from submitting and merging malicious changes to the pipeline without proper review.
Why C is Wrong: Retraining with more data and epochs addresses model performance restoration after the fact but does not prevent future unauthorized pipeline modifications. If the pipeline remains unprotected, the same attack could occur again on the new model.
Why D is Wrong: Keeping multiple model copies enables rapid restoration of a previous version when a deployed model is found to be compromised. While useful for recovery, it is a reactive measure that does not prevent unauthorized pipeline changes from occurring and affecting future model training.
NEW QUESTION # 111
A short AI-generated video shows a celebrity's likeness talking about a fake public security event.
Which of the following was used to create this video?
Answer: D
Explanation:
Convolutional neural networks (CNNs) are commonly used in generating deepfake videos, where a person's likeness is realistically mapped and animated to create fake but convincing audiovisual content.
NEW QUESTION # 112
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