Packt

AI Security Architecture, Controls, and Defensive Operations

Packt

AI Security Architecture, Controls, and Defensive Operations

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Implement AI threat modeling frameworks and risk assessment strategies for secure AI deployments.

  • Apply AI security controls including model guardrails, access management, and data protection measures.

  • Detect, prevent, and mitigate AI attack vectors such as prompt injections, model theft, and bias exploitation.

  • Leverage AI-enabled security tools to monitor, audit, and enhance organizational AI defenses.

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Recently updated!

March 2026

Assessments

11 assignments

Taught in English

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This course is part of the CompTIA SecAI+ (CY0-001) Certification Exam Prep Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 9 modules in this course

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.

What's included

7 videos2 readings1 assignment

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.

What's included

10 videos1 assignment

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.

What's included

4 videos1 assignment

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.

What's included

8 videos1 assignment

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.

What's included

7 videos1 assignment

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.

What's included

20 videos1 assignment

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.

What's included

8 videos1 assignment

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.

What's included

7 videos1 assignment

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.

What's included

11 videos1 reading3 assignments

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Instructor

Packt - Course Instructors
Packt
2,023 Courses611,541 learners

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