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PODCAST

Certified - AI Security Audio Course

The AI Security & Threats Audio Course is a comprehensive, audio-first learning series focused on the risks, defenses, and governance models that define secure artificial intelligence operations today. Designed for cybersecurity professionals, AI practitioners, and certification candidates, this course translates complex technical and policy concepts into clear, practical lessons. Each episode explores a critical aspect of AI security—from prompt injection and model theft to data poisoning,

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All Episodes

26:48

Episode 11 — Privacy-Preserving Techniques

Certified - AI Security Audio Course ·

2025/09/15

This episode explores privacy-preserving techniques designed to reduce the risk of sensitive information exposure in AI systems while maintaining utility of the models. Learners must understand concepts such as anonymization, pseudonymization, and data minimization, which limit identifiable information in training sets. Differential privacy is introduced as a mathematical framework that injects statistical noise into data or queries, providing measurable privacy guarantees. Federated

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27:38

Episode 10 — Privacy Attacks

Certified - AI Security Audio Course ·

2025/09/15

This episode introduces privacy attacks in AI systems, focusing on techniques that reveal sensitive or personal information from training data or model behavior. Learners must be able to define key attack types, such as membership inference—determining whether a specific record was included in training—and model inversion, where attackers reconstruct approximate training inputs. The exam relevance lies in understanding not only the mechanics of these attacks but also their implications for

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21:46

Episode 9 — Training-Time Integrity

Certified - AI Security Audio Course ·

2025/09/15

This episode covers training-time integrity, focusing on the assurance that data, processes, and infrastructure used in model development remain uncompromised. Learners preparing for exams must understand that threats at this stage include data tampering, corrupted labels, or manipulated hyperparameters. Unlike inference-time attacks, which target deployed models, training-time compromises affect the foundation of the model itself, potentially embedding vulnerabilities that persist

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24:10

Episode 8 — Data Poisoning Attacks

Certified - AI Security Audio Course ·

2025/09/15

This episode introduces data poisoning as a high-priority threat in AI security, where adversaries deliberately insert malicious samples into training or fine-tuning datasets. For exam readiness, learners must understand how poisoning undermines model accuracy, introduces backdoors, or biases outputs toward attacker goals. The relevance of poisoning lies in its persistence, as compromised models may behave unpredictably long after training is complete. Definitions such as targeted versus

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20:37

Episode 7 — Content Safety vs. Security

Certified - AI Security Audio Course ·

2025/09/15

This episode explains the distinction and overlap between content safety and security in AI systems, a concept often emphasized in both professional practice and certification exams. Content safety refers to filtering or moderating outputs to prevent harmful or offensive material, while security focuses on protecting systems and assets from adversarial manipulation or data loss. Although they are related, treating them as identical can cause organizations to miss critical risks. Learners

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22:07

Episode 6 — Prompt Security II: Indirect &...

Certified - AI Security Audio Course ·

2025/09/15

This episode examines indirect and cross-domain prompt injections, which expand the attack surface by embedding malicious instructions in external sources such as documents, websites, or email content. Unlike direct injection, where the attacker provides inputs to the model directly, these threats exploit retrieval or integration features that feed information into the AI system automatically. Learners preparing for certification exams must understand the mechanics of these attacks, which

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22:25

Episode 5 — Prompt Security I: Injection & Jailbreaks

Certified - AI Security Audio Course ·

2025/09/15

This episode introduces prompt injection and jailbreaks as fundamental AI-specific security risks. It defines prompt injection as malicious manipulation of model inputs to alter behavior and describes jailbreaks as methods for bypassing built-in safeguards. For certification purposes, learners must understand these concepts as new categories of vulnerabilities unique to AI, distinct from but conceptually parallel to classical injection attacks. The discussion highlights why prompt injection

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23:51

Episode 4 — Data Lifecycle Security

Certified - AI Security Audio Course ·

2025/09/15

This episode examines data lifecycle security, covering the journey of data from collection and labeling through storage, retention, deletion, and provenance management. It explains why data is the foundation of AI system reliability and how its misuse or compromise undermines security objectives. For certification preparation, learners are introduced to key definitions of provenance, integrity, and retention policies, while understanding how regulatory requirements drive data governance

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21:49

Episode 3 — System Architecture & Trust Boundaries

Certified - AI Security Audio Course ·

2025/09/15

This episode explains the architecture of AI systems, breaking down their stages and components to show how trust boundaries shift across the lifecycle. Training, inference, retrieval-augmented generation (RAG), and agent frameworks are introduced as discrete but interconnected environments, each with distinct risks. For exam relevance, learners are expected to identify these architectural elements, describe where threats occur, and understand how adversaries exploit them. The discussion

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23:14

Episode 2 — The AI Security Landscape

Certified - AI Security Audio Course ·

2025/09/15

This episode defines the AI security landscape by mapping the assets, attack surfaces, and emerging threats that distinguish AI from classical application security. It introduces critical components such as training data, model weights, prompts, and external tools, explaining why each must be protected as an asset. The relevance for certification exams lies in understanding how these components shift trust boundaries and create new risks compared to traditional software systems. The episode

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21:42

Episode 1 — Course Overview & How to Use This Prepcast

Certified - AI Security Audio Course ·

2025/09/15

This opening episode provides a structured orientation to the AI Security and Threats Audio course series, helping listeners understand what the program covers and how to best engage with the material. The overview defines the scope of AI security by placing it within the broader context of cybersecurity and risk management, while clarifying the distinctive elements that make AI-specific security necessary. It explains how the episodes are organized, moving from foundational principles

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51 results

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