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CompTIA certification

CompTIA SecAI+

Secure, govern, and responsibly integrate AI into cybersecurity operations.CompTIA SecAI+ is the first certification in CompTIA's expansion series, designed to help you secure, govern and responsibly integrate artificial intelligence into your cybersecurity operations. You'll build the skills to defend AI systems, meet global compliance expectations and use AI to enhance threat detection, automation and innovation, so you can strengthen your expertise and help keep your organization's systems and data secure.
CompTIA
Exam version: V1
Target roleSecurity engineer, security architect, security analyst

Skills you'll

learn

Build skills with CompTIA learning and validate them with the CompTIA SecAI+ certification.
Apply AI concepts to strengthen your organization's cybersecurity posture.
Secure AI systems using advanced controls and protections to safeguard data, models, and infrastructure.
Leverage AI technologies to automate workflows, accelerate incident response, and scale security operations.
Navigate global GRC frameworks to ensure ethical and compliant AI adoption across industries.
Defend against AI-driven threats like adversarial attacks, automated malware, and malicious use of generative AI.
Integrate AI securely into DevSecOps pipelines and enterprise security strategies.

Exam

details

Everything you need to know before taking the CompTIA SecAI+ exam.
Exam versionV1
Exam series codeCY0-001
Launch dateFebruary 17, 2026
Number of questionsMaximum of 60 questions
Types of questionsMultiple-choice and performance-based
Duration60 minutes
Passing score600 (on a scale of 100–900)
LanguagesEnglish and Japanese
Recommended experience3–4 years in IT and 2+ years of hands-on cybersecurity; Security+, CySA+, PenTest+, or equivalent recommended
RetirementEstimated three years after launch

Exam

objectives

The CompTIA SecAI+ (V1) exam covers the following domains, weighted by their share of the exam.
1

Basic AI concepts related to cybersecurity

17%
  • Explain core AI principles and terminology: machine learning, deep learning, natural language processing, and automation.
  • Identify AI applications in security: use cases for AI in threat detection, defense, and security operations.
  • Recognize AI-driven threats: automated phishing, polymorphic malware, adversarial machine learning, and malicious use of generative AI.
2

Securing AI systems

40%
  • Implement security controls: protect AI systems, data, and models using robust technical safeguards.
  • Secure AI deployment environments: apply best practices across on-premises, cloud, and hybrid infrastructures.
  • Mitigate adversarial risks: defend against attacks targeting AI models, data pipelines, and inference layers.
3

AI-assisted security

24%
  • Enhance detection and response: use AI-driven tools to identify anomalies, detect threats, and accelerate incident remediation.
  • Automate security workflows: integrate AI for event triage, alert correlation, and response orchestration.
  • Apply AI techniques in operations: incorporate AI into threat modeling, behavior analysis, and continuous monitoring.
4

AI governance, risk, and compliance

19%
  • Understand regulatory frameworks: identify global governance requirements and their implications for AI adoption.
  • Integrate GRC into AI projects: incorporate governance, risk management, and compliance practices throughout the AI lifecycle.
  • Ensure responsible AI use: apply ethical guidelines, legal standards, and industry frameworks such as GDPR and NIST AI RMF.
Exam information is published by CompTIA and may change. Contact us for the current exam version and available sessions.

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