CompTIA SecAI+ CY0-001 study board

CompTIA SecAI+ CY0-001: every exam objective on a hand-drawn mind map, 988 flashcards and 840 practice questions. Free preview, $29.99 one-time.

Exam version: Follows CompTIA's SecAI+ CY0-001 (V1) exam objectives. CY0-001 launched 17 February 2026.

What you get

• 33 hand-drawn sheets: every exam objective on its own sheet, in reading order
• 988 flashcards written from the cards on the map, that come back just before you'd forget
• 840 original practice questions, each graded with the answer explained
• A Treemap of every card the flashcards and practice questions cover, painted by the score you have earned on it, so you can see what is left
• Bookmarks and sticky notes, saved to your account
• One payment of $29.99: no subscription, no expiry date

Who it is for

People studying for CompTIA SecAI+ CY0-001 on their own who learn best by seeing how topics connect, and who want one place to read the map, recall it with flashcards, prove it on practice questions and see their progress on a Treemap.

Who it is not for

It is not a hands-on lab, not a full video course and not a replacement for practising on real equipment or software.

Free preview: what is on the board

• Start here
  • How to use this map
    • Big idea: learn the decision, not the definition
    • One sheet per sitting
    • Getting around the SecAI+ map
    • Reading a card
    • Marks on the SecAI+ map
    • Read the objective's verb first
  • The exam at a glance
    • Big idea: a first-version exam on a moving target
    • Where the CY0-001 marks are
    • Domain weights and what they ask
    • SecAI+ exam-day facts
    • Performance-based questions
    • What the exam assumes you know
    • Standards this map leans on
• Basic AI Concepts Related to Cybersecurity (17%)
  • 1.1a Types of AI
    • Big idea: rules are written, models are learned
    • Which kind of AI fits the task?
    • AI, ML, deep learning, statistics
    • Generative models
    • Language models (NLP)
    • Check yourself: types of AI
  • 1.1b Model training techniques
    • Big idea: the data you have picks the method
    • Which training approach fits?
    • Ways a model learns
    • Did it learn or memorise?
    • Fine-tuning and slimming
    • Check yourself: training techniques
  • 1.1c Prompt engineering
    • Big idea: the prompt is the program
    • How many examples should the prompt carry?
    • Who says what
    • Zero, one or many examples
    • Templates
    • Check yourself: prompt engineering
  • 1.2a Data processing and data types
  • 1.2b Watermarking and RAG
  • 1.3a Life cycle: plan, collect, prepare, build
  • 1.3b Life cycle: evaluate, deploy, run
  • 1.3c Human-centric AI design
• Securing AI Systems (40%)
  • 2.1a OWASP Top 10 lists for AI
  • 2.1b ATLAS, MIT, CVE and threat models
  • 2.2a Model controls and guardrail tests
  • 2.2b Gateway controls
  • 2.3 Access controls for AI systems
  • 2.4 Data security controls for AI
  • 2.5a Prompts, logs and confidence
  • 2.5b Rate, cost and quality audits
  • 2.6a Attacks on data and models
  • 2.6b Attacks on prompts and tools
  • 2.6c Evidence to compensating controls
• AI-assisted Security (24%)
  • 3.1a AI tools in the security workflow
  • 3.1b AI security use cases
  • 3.2a Deepfakes, GANs and AI social engineering
  • 3.2b AI-automated attacks
  • 3.3a Automating security operations with AI
  • 3.3b AI in the CI/CD pipeline
• AI Governance, Risk, and Compliance (19%)
  • 4.1 AI governance structures and roles
  • 4.2a Responsible AI principles
  • 4.2b AI business risks and shadow AI
  • 4.3a EU AI Act and privacy law
  • 4.3b AI frameworks and standards
  • 4.3c AI policy, audits and sovereignty

Sample flashcard

When choosing which kind of AI fits a security task, what is the first question to ask, and where does each answer lead?

Ask whether the task must create new content. Yes leads to generative models (a transformer language model for text, code or chat; a GAN or similar generator for images or voice). No leads on to asking whether the input is human language, then whether it is raw high-volume data, then whether every decision must be explained.

Sample practice question

Which statement correctly describes how artificial intelligence, machine learning and deep learning relate to one another?

• A. Machine learning is a kind of deep learning, which is one way of building AI
• B. Deep learning and machine learning are separate approaches to AI that do not overlap
• C. AI is a kind of machine learning that uses deep neural networks
• D. Deep learning is a kind of machine learning, which is one way of building AI

Answer: D. AI is the umbrella term; machine learning is one way of achieving it, by learning behaviour from data; deep learning is the subset of ML that uses neural networks with many layers. Putting ML inside DL reverses the nesting. AI is not a kind of ML, and DL cannot be separate from ML because every deep network is trained from data, which is what makes it ML.

Questions

Do I download the CompTIA SecAI+ CY0-001 board?

No. Boards open on the website in your browser, on a computer or a phone, once you sign in. Your flashcard progress, bookmarks and test results are saved to your account.

How long do I keep access?

It is a one-time purchase with no subscription and no expiry date.

Can I try it before I buy?

Yes. Every board has a free preview: the introduction, the first three sheets of the first domain and ten sample questions, with no account needed.

What if the exam changes?

This board follows one exam version (CY0-001). Check that it matches the exam you are booking before you buy.

What is the refund policy?

You can ask for a refund within 7 days of buying, with no reason needed. Details are in the Refund Policy.

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