SecAI+ Exam Prep: Complete Guide to CompTIA SecAI+

The CompTIA SecAI+ (CY0-001) is the first vendor-neutral certification built at the intersection of artificial intelligence and cybersecurity. It launched February 17, 2026, and validates that you can secure AI systems, defend against AI-driven threats, leverage AI for security operations, and govern AI responsibly within an enterprise environment. This course is the most complete exam preparation resource available for it.

Across 17 sections and 82 modules, every official CY0-001 exam objective from Version 2. 0 of the CompTIA SecAI+ syllabus is covered in full. The course is structured to mirror the official domain weighting so you always know where your study time is going: Basic AI Concepts Related to Cybersecurity (17%), Securing AI Systems (40%), AI-Assisted Security (24%), and AI Governance, Risk and Compliance (19%).

Domain 1 builds your AI foundation from scratch. You will cover AI types including generative AI, machine learning, deep learning, transformers, LLMs, SLMs, and GANs, followed by prompt engineering techniques, data security in AI pipelines, RAG architecture, vector storage, embeddings, and security across the full AI development lifecycle. Domain 2, the most heavily weighted domain at 40%, is where most candidates struggle and where this course goes deepest.

You will work through AI-specific threat modeling using the OWASP LLM Top 10, OWASP ML Security Top 10, MITRE ATLAS, and the MIT AI Risk Repository. You will then cover every category of security control for AI systems: model guardrails, prompt firewalls, rate and token limits, access controls for models, data, agents and APIs, data security including encryption in transit, at rest and in use, and monitoring and auditing for AI quality and compliance. The AI attack taxonomy is covered in full across dedicated modules: prompt injection, indirect prompt injection, jailbreaking, model poisoning, data poisoning, hallucination exploitation, input manipulation, bias injection, guardrail bypass, model inversion, model theft, membership inference, AI supply chain attacks, transfer learning attacks, model skewing, output integrity attacks, insecure plug-in design, excessive agency, and model denial of service.

Every attack type is paired with its specific compensating controls so you can answer scenario-based and performance-based questions with confidence. Domain 3 covers how AI enables and enhances both defensive and offensive security operations: AI-powered tools including IDE plug-ins, browser plug-ins, CLI plug-ins, MCP servers, and chatbots, AI-driven attack vectors including deepfakes, AI-generated payloads, automated reconnaissance, and AI-enhanced social engineering, and automation of security tasks through low-code scripting, document synthesis, incident ticket management, AI agents, and CI/CD pipeline security. Domain 4 covers the governance, risk, and compliance frameworks that now govern enterprise AI adoption globally: the EU AI Act risk tiers and compliance obligations, OECD AI principles, ISO 42001 and ISO 23894, the NIST AI Risk Management Framework across all four functions, responsible AI principles, AI risk categories including shadow AI and autonomous system risk, corporate AI policy, data sovereignty, private versus public model governance, third-party AI compliance evaluation, and GDPR applied to AI systems.

Every module closes with scenario-based application and targeted exam tips mapped to the specific CY0-001 objective. The SecAI+ is a new certification. Passing it in 2026 positions you ahead of the vast majority of the cybersecurity workforce in a specialization that is already creating dedicated job roles and increasing salary premiums across the industry.