AI Security Architecture, Controls, and Defensive Operations

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Overview

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This comprehensive course equips learners with the knowledge and skills to secure AI systems effectively, covering threat modeling, security controls, access management, data protection, monitoring, and attack mitigation. You’ll explore practical frameworks like OWASP ML Security Top 10, MITRE ATLAS, and CVE AI guidelines, gaining hands-on insights into implementing robust AI defenses. Through structured modules, learners will understand model evaluation, guardrails, endpoint access, encryption, auditing, and monitoring practices essential for safeguarding AI deployments. The course also examines real-world attack vectors including prompt injection, model inversion, supply chain threats, and adversarial manipulations, teaching you how to anticipate, detect, and mitigate risks. Designed for IT professionals, security engineers, and AI practitioners, this course assumes foundational knowledge in cybersecurity principles and AI systems, offering a structured path from basic controls to advanced defensive strategies. By the end of the course, you will be able to design, implement, and manage comprehensive AI security architectures, apply controls and compensating measures, secure data and access, and utilize AI-enabled tools to protect systems from complex attack vectors.

Syllabus

CompTIA SecAI+ AI Threat Modeling Certification Guide

In this module, we will introduce learners to AI threat modeling and its role in protecting AI systems. We will explore OWASP’s top AI security risks, MIT AI repositories, and the MITRE ATLAS framework. Additionally, learners will gain insight into threat modeling frameworks and how to apply them effectively for AI security.

CompTIA SecAI+ AI Security Controls Certification Guide

In this module, we will cover the full range of AI security controls required for robust defenses. Learners will explore model evaluation, guardrails, gateway controls, rate limits, and token limitations. We will also discuss input, modality, and endpoint controls to ensure comprehensive AI security.

CompTIA SecAI+ AI Access Controls Certification Guide

In this module, we will examine access control mechanisms critical for AI security. Learners will understand how to manage model, data, and agent permissions effectively. We will also cover network and API controls to protect AI systems from unauthorized access.

CompTIA SecAI+ AI Data Security Controls Guide

In this module, we will explore AI data security practices that ensure confidentiality and integrity. Learners will cover encryption at rest, in use, and in transit, along with anonymization and data labeling strategies. We will also discuss redaction, masking, and minimization principles to strengthen AI data security.

CompTIA SecAI+ AI Monitoring and Auditing Guide

In this module, we will focus on AI monitoring and auditing techniques. Learners will explore prompt monitoring, log management, response confidence tracking, and rate monitoring. We will also cover auditing for quality and compliance to ensure secure and efficient AI operations.

CompTIA SecAI+ AI Attack Vectors Certification Guide

In this module, we will explore the various attack vectors targeting AI systems. Learners will examine prompt injection, model/data poisoning, jailbreaking, hallucinations, and bias risks. We will also cover advanced attacks such as model inversion, theft, DoS, and supply chain threats, along with mitigation strategies.

CompTIA SecAI+ AI Compensating Controls Guide

In this module, we will cover compensating controls designed to secure AI systems. Learners will explore prompt firewalls, model guardrails, access controls, data integrity measures, and encryption implementation. Strategies for least privilege and rate limiting will also be discussed to reinforce AI defenses.

CompTIA SecAI+ AI-Enabled Security Tools Guide

In this module, we will introduce AI-enabled tools for strengthening security operations. Learners will explore browser, CLI, and IDE plug-ins, AI chatbots, personal assistants, and MCP servers. We will also discuss how these tools help secure AI systems while improving operational efficiency.

CompTIA SecAI+ AI Security Use Cases Guide

In this module, we will explore practical AI applications in security operations. Learners will examine use cases such as signature matching, anomaly detection, threat modeling, and fraud detection. We will also cover AI-driven vulnerability analysis, automated penetration testing, and incident management to reinforce real-world security expertise.