CompTIA SecAI+ (CY0-001) Complete Course: AI Security

Achieve success in the SecAI+ exam by securing LLMs, RAG, and AI agents, preventing prompt injection, and mastering AI governance and compliance.

  • All Levels
  • 8 sections · 101 lessons · 13h 38m total
  • Online, self-paced

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CompTIA SecAI+ (CY0-001) Complete Course: AI Security

What you'll learn

  • Prepare thoroughly for the CompTIA SecAI+ (CY0-001) exam with complete understanding of all four domains and every objective of the exam.
  • Clarify how machine learning, generative AI, LLMs, transformers, and RAG function, and identify the security risks associated with each.
  • Create AI threat models utilizing the OWASP Top 10 for LLM Applications, the OWASP ML Security Top 10, and MITRE ATLAS.
  • Protect AI and LLM applications against threats such as prompt injection, jailbreaks, data poisoning, model theft, and other attacks.
  • Establish layered AI security controls including guardrails, AI gateways, prompt firewalls, input/output validation, and rate limits.
  • Implement principles of least privilege, access controls, encryption, and data masking in relation to AI models, AI agents, APIs, MCP servers, and RAG.
  • Oversee, log, and audit AI systems to identify misuse, hallucinations, excessive token costs, and security incidents related to AI.
  • Utilize AI in a secure manner for activities such as security operations, vulnerability analysis, and automation, ensuring human oversight over AI agents.
  • Identify AI-powered cyber threats including deepfakes, AI-driven phishing, automated reconnaissance, and AI malware.
  • Develop AI governance, risk, and compliance programs referencing the EU AI Act, NIST AI RMF, ISO/IEC 42001, and OECD principles.
  • Engage in real-world decision-making through practical exercises, an ongoing banking case study, and downloadable AI security worksheets.

Course outline

8 sections · 101 lessons · 13h 38m total

Introduction to CompTIA SecAI+ 5 lessons · 30m
  1. Welcome to CompTIA SecAI+ (CY0-001) Free Preview On Udemy 05:36
  2. Understanding the Exam Structure and Four Domains 06:07
  3. Who Needs AI Security Skills and Why 05:16
  4. The Three Dimensions of AI Cybersecurity 06:33
  5. Introducing Our Continuing Case Study 06:53
AI Foundations for Cybersecurity 16 lessons · 2h 3m
  1. Artificial Intelligence, Machine Learning, and Statistical Learning Free Preview On Udemy 06:54
  2. Generative AI and Its Role in Cybersecurity 06:43
  3. Deep Learning, Neural Networks, and Transformers 06:26
  4. Natural Language Processing and Language Models 06:57
  5. Large Language Models vs. Small Language Models 06:36
  6. Generative Adversarial Networks and Security Applications 06:02
  7. Supervised, Unsupervised, and Reinforcement Learning 09:07
  8. ACTIVITY: Choose the AI Technique 05:59
  9. Federated Learning and Distributed Training Security 08:22
  10. ACTIVITY: Centralized or Federated? 07:06
  11. Model Training, Validation, and Fine-Tuning 09:18
  12. Understanding Epochs, Pruning, and Quantization 07:07
  13. Prompt Engineering: System Prompts, User Prompts, and Roles 07:46
  14. Zero-Shot, One-Shot, and Multi-Shot Prompting 07:09
  15. Prompt Templates and Secure Prompt Design 07:20
  16. AI Data Security and the AI Lifecycle 14:00
AI Threat Modeling and Security Frameworks 11 lessons · 1h 32m
  1. Why Traditional Threat Modeling Is Not Enough for AI Free Preview On Udemy 08:09
  2. Understanding AI Attack Surfaces and Trust Boundaries 07:50
  3. OWASP Top 10 for Large Language Model Applications 08:19
  4. OWASP Machine Learning Security Top 10 09:07
  5. MITRE ATLAS: Adversarial Threats to AI Systems 08:09
  6. Understanding the MIT AI Risk Repository 08:14
  7. Common Vulnerabilities and Exposures (CVE) and AI Vulnerabilities 08:56
  8. Applying Threat Modeling Frameworks to AI Architectures 08:27
  9. Building an AI Threat Model Step by Step 09:40
  10. ACTIVITY: Threat Model the Customer Assistant 07:02
  11. Prioritizing AI Threats and Selecting Mitigations 08:35
AI Security Architecture, Guardrails, and Gateway Controls 12 lessons · 1h 40m
  1. Designing Defense-in-Depth for AI Applications Free Preview On Udemy 07:38
  2. Model Evaluation as a Security Control 07:47
  3. Understanding Model Guardrails 07:33
  4. Input Validation and Secure Prompt Templates 08:23
  5. Output Validation and Response Filtering 08:36
  6. AI Gateways and Security Enforcement Points 09:24
  7. Prompt Firewalls and Injection Defense 08:22
  8. Rate Limiting and Token Limits 08:53
  9. Input Quotas: Data Size and Request Quantity 09:01
  10. Modality Restrictions and Endpoint Access Controls 08:11
  11. Testing, Validating, and Improving AI Guardrails 08:31
  12. ACTIVITY: Select Layered Controls 07:37
AI Access Controls and Data Protection 12 lessons · 1h 31m
  1. Identity and Access Management for AI Systems Free Preview On Udemy 07:06
  2. Model Access Controls and Authorization 07:12
  3. Securing AI Training and Inference Data Access 07:10
  4. AI Agent Permissions and Least Privilege 07:57
  5. Network and API Access Controls 07:51
  6. Authentication, Authorization, and Service Identities 06:48
  7. Encryption in Transit, at Rest, and in Use 08:14
  8. Data Classification and Sensitive Data Labels 07:13
  9. Data Masking, Redaction, and Anonymization 07:39
  10. Data Minimization and Privacy-by-Design 07:49
  11. Applying Access Controls to RAG and Agentic AI Systems 08:50
  12. ACTIVITY: Review AI Access 07:25
AI Monitoring, Logging, and Security Auditing 12 lessons · 1h 40m
  1. Why AI Systems Require Specialized Monitoring Free Preview On Udemy 08:16
  2. Monitoring Prompts, Queries, and Model Responses 08:59
  3. Logging AI Application and Model Activity 08:30
  4. Log Sanitization and Sensitive Information Protection 07:42
  5. Log Integrity, Retention, and Access Protection 08:05
  6. Response Confidence and Model Reliability 07:21
  7. Monitoring Request Rates and Resource Consumption 09:22
  8. AI Cost Monitoring: Tokens, Storage, and Processing 09:00
  9. Detecting Hallucinations and Accuracy Problems 08:00
  10. Auditing AI Bias, Fairness, and Access 08:57
  11. Building an AI Security Monitoring Dashboard 09:26
  12. ACTIVITY: Analyze AI Logs 06:39
AI Attacks, Exploitation, and Compensating Controls 19 lessons · 2h 45m
  1. Understanding the AI Threat Landscape Free Preview On Udemy 08:51
  2. Direct and Indirect Prompt Injection Attacks 08:43
  3. Jailbreaking and Guardrail Bypass Techniques 07:57
  4. Data Poisoning and Model Poisoning 08:37
  5. Backdoor and Trojan Attacks in AI Models 08:47
  6. ACTIVITY: Investigate a Model Compromise 08:02
  7. Input Manipulation and Adversarial Examples 08:46
  8. Model Inversion and Membership Inference 08:23
  9. Model Theft and Extraction Attacks 08:50
  10. AI Supply Chain and Transfer Learning Attacks 09:42
  11. Model Skewing, Bias Manipulation, and Output Integrity Attacks 09:04
  12. Sensitive Information Disclosure and Insecure Output Handling 08:37
  13. Insecure Plugins and Application Integrations 08:21
  14. Excessive Agency and Unauthorized Agent Actions 07:35
  15. Model Denial-of-Service and Resource Exhaustion 08:32
  16. Hallucinations, Overreliance, and Unsafe Decisions 07:57
  17. Matching AI Attacks to Compensating Controls 08:36
  18. Analyzing Evidence of AI Security Incidents 10:38
  19. ACTIVITY: Investigate a Prompt Injection Incident 08:54
AI-Enabled Cybersecurity Tools and Applications 14 lessons · 1h 56m
  1. How AI Is Transforming Security Operations Free Preview On Udemy 07:46
  2. AI-Enabled Chatbots and Security Assistants 07:22
  3. AI Plugins for IDEs, Browsers, and Command-Line Tools 07:15
  4. ACTIVITY: Review an MCP Permission Boundary 07:11
  5. AI-Assisted Signature Matching and Pattern Recognition 09:00
  6. AI for Code Quality, Linting, and Security Reviews 08:35
  7. AI-Assisted Vulnerability Analysis 08:49
  8. AI in Automated Penetration Testing 08:43
  9. Anomaly Detection and Behavioral Analysis 09:01
  10. AI-Assisted Incident Management and Threat Modeling 08:52
  11. AI for Fraud Detection and Suspicious Activity Analysis 08:32
  12. Security Document Summarization and Translation 08:27
  13. Validating AI-Generated Security Findings 09:18
  14. ACTIVITY: Validate an AI Vulnerability Report 07:12

About this course

This course focuses on leveraging artificial intelligence.

AI has become integral to most security frameworks, and cybercriminals are utilizing it as well. The CompTIA SecAI+ (CY0-001) certification affirms your capability to safeguard AI systems, employ AI for defensive strategies, and protect against AI-enabled threats. This comprehensive video course readies you for the exam and equips you for practical application.

You will learn through a continuous case study featuring Meridian, a fictional financial organization, as it implements a customer assistant, an internal knowledge assistant, and incorporates AI within its security operations center. Each concept relates to real-world decisions a security professional must address.

Course Content

  • Fundamentals of AI for security: machine learning, generative AI, large language models (LLMs), transformers, retrieval-augmented generation (RAG), and secure prompt engineering.
  • Protection of AI systems: AI threat modeling following the OWASP Top 10 for LLM Applications, MITRE ATLAS, guardrails, AI gateways, prompt firewalls, rates and token limits, access controls for AI agents and MCP servers, data protection, alongside AI monitoring and logging.
  • AI threats and countermeasures: prompt injection, jailbreaks, data poisoning, backdoors, model theft, model inversion, membership inference, and the compensating controls that mitigate these risks.
  • AI-fortified security: tools for AI security, SOC automation, vulnerability assessments, AI-enhanced phishing, deepfakes, and human-supervised AI agents.
  • Governance, risk, and compliance regarding AI: the EU AI Act, NIST AI Risk Management Framework, ISO/IEC 42001, OECD AI Principles, shadow AI, third-party AI risk, and data sovereignty.

Distinctive Features of This Course

  • 178 targeted lessons that comprehensively cover all four domains of the SecAI+ exam.
  • Practical activities allowing you to make decisions and then compare them with the underlying reasoning.
  • Downloadable worksheets and templates related to AI security, such as threat models, access reviews, log audits, and governance maturity assessments.
  • A final review section that includes domain-by-domain summaries, strategies for performance-based questions, and preparation for exam day.

Whether you are gearing up for the SecAI+ exam or looking to secure AI within your organization, you will come away with the ability to articulate AI risks, select appropriate controls, and substantiate your decisions with evidence.

CompTIA and SecAI+ are trademarks of CompTIA, Inc. This course is not affiliated with, endorsed by, or sponsored by CompTIA.

Who this course is for

  • Cybersecurity professionals studying for the CompTIA SecAI+ (CY0-001) certification exam.
  • SOC analysts, security engineers, and penetration testers tasked with securing AI systems or combating AI-driven threats.
  • Security architects, cloud engineers, and developers involved in building or implementing LLM, RAG, and agentic AI applications.
  • GRC, risk, compliance, and audit professionals overseeing AI governance, adherence to the EU AI Act, and the NIST AI RMF.
  • IT managers and security authorities in need of a hands-on framework for the responsible integration of AI.

CompTIA SecAI+ (CY0-001) Complete Course: AI Security

Get On Udemy (opens in a new tab)