About the Exam

CompTIA SecAI+ is a cybersecurity certification exam focused on AI concepts, securing AI systems, using AI to support security work, and AI governance, risk, and compliance. The exam is aimed at IT professionals with roughly 3-4 years of IT experience and about 2 years of hands-on cybersecurity experience. It uses multiple-choice and performance-based questions. Passing demonstrates practical knowledge of protecting AI-enabled systems and applying AI in cybersecurity operations.

Exam Topics

  • Basic AI concepts related to cybersecurity17%
  • Securing AI systems40%
  • AI-assisted security24%
  • AI governance, risk, and compliance19%

How to Use This Practice Exam

  1. Browse — Read each question, select your answer, and reveal the explanation.
  2. Exam Mode — Simulate real exam conditions with a timed session and score report.
  3. Learn Mode — Spaced repetition schedules questions you struggle with for long-term retention.

Download the Full Exam PDF

Get every question and answer in a clean, printable PDF built for offline study. Purchase once, keep permanent access, and re-download the latest version anytime.

Last updated May 14, 2026 at 7:38 PM

Topic filter
Retired questions
Question sort
Questions per page

QuestionQ1

Basic AI concepts related to cybersecurity

While selecting an ML-based threat-classification model, a cybersecurity administrator confirms that the label distribution is highly imbalanced. Which of the following processing techniques should the engineer use to balance the model?

Explanation

Data augmentation increases the number and diversity of training examples, particularly for underrepresented classes, which helps address an imbalanced label distribution.

Community Discussion

No comments yet. Be the first to start the discussion!

QuestionQ2

Securing AI systems

An ML engineer is collaborating with a security engineer to determine best practices for securing a system that contains various AI models.

Which of the following actions should the engineers recommend?

Choose four
Explanation

Securing AI systems requires defense in depth across both AI-specific and traditional components. This includes testing guardrails and security behavior, applying lifecycle security controls to models and data, designing a comprehensive security architecture, and using a secure SDLC for the software that builds, integrates, deploys, and operates the models.

Learn more

Community Discussion

No comments yet. Be the first to start the discussion!

QuestionQ3

AI-assisted security

A security team is using an AI-based tool in an attempt to bypass organizational boundaries. The team uses AI to assess the current state and recommend different attack vectors based on the results of earlier attempts. Which technique is the team most likely using?

Explanation

Automated penetration testing can use AI to evaluate the environment, adapt to the results of previous actions, and recommend or execute subsequent attack paths to test whether security boundaries can be bypassed.

Community Discussion

No comments yet. Be the first to start the discussion!

QuestionQ4

AI governance, risk, and compliance

A company is adopting AI and wants to establish policies and procedures that provide a structure for evaluating, publishing, and approving AI usage patterns. Which of the following should the company create to achieve this goal?

Explanation

An AI Center of Excellence provides centralized AI governance. It defines and enforces AI standards, implements processes to evaluate and prioritize AI requests, and creates reusable, approved assets and patterns for organization-wide use.

Learn more

Community Discussion

No comments yet. Be the first to start the discussion!

QuestionQ5

AI governance, risk, and compliance

An employee asks a consulting company to obtain a dataset containing age, ethnicity, and diabetes status. During development, the employer wants to ensure the data’s integrity. Which of the following is the best strategy for accomplishing this task?

Explanation

Checksums help verify data integrity by detecting corruption or unauthorized alteration: recalculating a checksum and comparing it with the expected value reveals whether the dataset has changed.

Community Discussion

No comments yet. Be the first to start the discussion!
Know a question that should be here? Contribute to this exam
Back home