All Episodes
Displaying 41 - 60 of 91 in total
Episode 50 — Use MITRE ATLAS Concepts for AI Threat Modeling and Adversary Behavior
This episode introduces MITRE ATLAS concepts as a structured way to think about adversary behavior against AI systems, because SecAI+ expects you to threat model AI li...
Episode 49 — Apply OWASP Guidance to ML Risks: Abuse Patterns and Defensive Responses
This episode focuses on machine learning risks beyond LLMs, because SecAI+ includes scenarios where traditional ML models support detection, classification, or decisi...
Episode 48 — Apply OWASP Guidance to LLM Risks: Top Threats and Key Controls
This episode translates OWASP guidance into SecAI+ exam-ready thinking, because you are expected to recognize common LLM threat patterns and choose practical controls...
Episode 47 — Operate Feedback Loops Safely: User Inputs, Reinforcement, and Toxic Drift
This episode teaches feedback loops as a risk area, because SecAI+ will test whether you understand how user feedback, retraining signals, and reinforcement mechanisms...
Episode 46 — Build Human Oversight That Works: Reviews, Approvals, and Accountability Points
This episode focuses on human oversight as an operational control, because SecAI+ expects you to design workflows where people are placed at the right decision points,...
Episode 45 — Plan Secure Maintenance: Patch Strategy, Versioning, and Rollback Discipline
This episode teaches maintenance as a disciplined security process, because SecAI+ scenarios often include model updates, dependency changes, or vendor refreshes that ...
Episode 44 — Control Model Exposure: Endpoints, APIs, Authentication, and Authorization Choices
This episode explains why exposing a model through endpoints and APIs is a high-impact attack surface, because SecAI+ will test whether you can select authentication,...
Episode 43 — Design Secure Deployment Paths: Environments, Isolation, and Integration Boundaries
This episode covers deployment architecture as a security control, because SecAI+ expects you to reason about where AI components run, what they can reach, and how en...
Episode 42 — Evaluate Models for Abuse: Misuse Paths, Safety Gaps, and Overreach Risks
This episode teaches abuse evaluation as a core SecAI+ skill, because exam questions frequently ask what to test and what to mitigate when a model could be used to gen...
Episode 41 — Select Models Securely: Capability Fit, Failure Modes, and Vendor Transparency
This episode focuses on choosing an AI model as a security decision, because SecAI+ scenarios often hinge on whether the selected model fits the intended use case with...
Episode 40 — Translate Requirements into Controls: Security, Privacy, and Reliability Criteria
This episode teaches the requirement-to-control translation that SecAI+ expects you to perform in scenario questions, because strong programs do not start with tools,...
Episode 39 — Anchor AI Security to Business Objectives: Use-Case Scope and Risk Appetite
This episode focuses on aligning AI security controls to business objectives, because SecAI+ often tests whether you can choose security requirements that fit the use ...
Episode 38 — Enforce Data Access Boundaries: RBAC, ABAC, and Purpose-Based Controls
This episode teaches access boundaries for AI data as a key exam topic, because SecAI+ expects you to prevent unauthorized use of sensitive data across teams, tools, a...
Episode 37 — Manage Data Retention: Deletion, Forgetting Limits, and Compliance-Driven Policies
This episode explains retention as both a legal requirement and an AI security requirement, because SecAI+ scenarios often involve data being kept “just in case” and l...
Episode 36 — Encrypt AI Data Correctly: In Transit, At Rest, and In Use
This episode focuses on encryption as a foundational control that SecAI+ expects you to apply with precision, because AI pipelines often move data across ingestion se...
Episode 35 — Protect Sensitive Data With Masking, Redaction, and Practical De-Identification
This episode teaches sensitive data protection as a hands-on discipline across the AI lifecycle, because SecAI+ will test whether you can reduce exposure without dest...
Episode 34 — Understand Watermarking Basics: Goals, Limits, and Validation Use Cases
This episode explains watermarking as a technique with specific goals and very real limits, because SecAI+ expects you to understand when watermarking supports securit...
Episode 33 — Preserve Integrity End-to-End: Hashing, Signing, and Controlled Transformations
This episode focuses on integrity controls that keep AI pipelines trustworthy, because SecAI+ scenarios often involve tampering risks that occur between “we collected...
Episode 32 — Build Lineage and Traceability: From Raw Sources to Model Artifacts
This episode teaches lineage and traceability as core AI security controls, because SecAI+ will test whether you can prove what went into a model, what changed over ti...
Episode 31 — Apply Data Augmentation Responsibly Without Introducing Backdoors or Skew
This episode explains data augmentation as a double-edged technique in SecAI+ terms, because it can improve robustness and coverage, but it can also introduce bias, di...