All Episodes

Episode 90 — Prevent Shadow AI: Sanctioned Tools, Usage Rules, and Enforcement Patterns

Episode 89 — Apply Responsible AI Principles: Fairness, Transparency, and Explainability Choices

Episode 88 — Define AI Security Responsibilities: Owners, Approvers, Builders, and Auditors

Episode 87 — Build AI Governance Structures: Policies, Roles, and a Working Operating Model

Episode 86 — Manage CI/CD With AI Assistants: Secure Pipelines, Tests, and Change Control

Episode 85 — Apply Safe Automation: Low-Code Workflows With Guardrails and Auditability

Episode 84 — Recognize AI-Assisted Malware Evolution: Obfuscation, Mutation, and Detection Gaps

Episode 83 — Track AI-Accelerated Recon: Target Discovery, Enumeration, and Defensive Signals

Episode 82 — Counter AI-Scaled Social Engineering: Phishing, Vishing, and Pretext Detection

Episode 81 — Understand AI-Driven Deepfakes: Impersonation Risk and Verification Countermeasures

Episode 80 — Use AI for Threat Intel: Entity Extraction, Clustering, and Confidence Handling

Episode 79 — Use AI for Incident Triage: Summaries, Prioritization, and Evidence Integrity

Episode 78 — Use AI for Detection Engineering: Rules, Correlation, and Noise Reduction

Episode 77 — Use AI for Code Review: Linting, SAST Triage, and False-Positive Control

Episode 76 — Use AI in Secure Coding: Generating Code Without Injecting Vulnerabilities

Episode 75 — Reduce Overreliance Risk: Human Verification Loops and Safe Escalation Rules

Episode 74 — Secure Integrations and Plug-Ins: Trust Boundaries, Validation, and Least Privilege

Episode 73 — Handle Denial-of-Service Risks: Model DoS, Cost Bombs, and Resilience

Episode 72 — Prevent Model Theft: Extraction Risks, Query Limits, and Watermark Strategies

Episode 71 — Analyze Membership Inference Risks: Privacy Exposure and Defensive Techniques

Episode 70 — Analyze Model Inversion Risks: What Can Leak and How to Reduce It

Episode 69 — Investigate Model Poisoning: Artifact Integrity, Supply Chain, and Remediation

Episode 68 — Investigate Data Poisoning: Detection Clues, Impact Analysis, and Recovery Steps

Episode 67 — Defend Against Jailbreaking: Common Tactics and Practical Mitigations

Episode 66 — Detect Prompt Injection Attempts: Indicators, Triage, and Containment Options

Episode 65 — Interpret Confidence Signals: Limits, Miscalibration, and Operational Risk

Episode 64 — Audit AI Use at Scale: Who Asked What, When, and With What Data

Episode 63 — Log AI Interactions Safely: Sanitization, Redaction, and Tamper-Resistance

Episode 62 — Monitor Prompts as Telemetry: Signals, Patterns, and Threat-Hunting Hooks

Episode 61 — Apply Key Management Right: Rotation, Storage, and Separation of Duties

Episode 60 — Apply Access Controls Across Layers: Data, Models, Tools, and Agents

Episode 59 — Lock Down Endpoints: Network Controls, Segmentation, and Service Hardening

Episode 58 — Secure Agent Toolchains: Least Privilege, Scoped Credentials, and Audit Trails

Episode 57 — Control Outputs Safely: Dangerous Content Filters and Secure Output Encoding

Episode 56 — Validate Inputs Rigorously: File Types, Length Limits, and Content Sanitization

Episode 55 — Set Rate Limits and Quotas: Token Caps, Cost Controls, and Abuse Prevention

Episode 54 — Build Prompt Firewalls: Filtering, Classification, and Instruction Boundary Checks

Episode 53 — Implement Guardrails That Hold: Policy Rules, Validators, and Refusal Logic

Episode 52 — Model the Attack Surface: Data, Model, Agent, Tooling, and Integrations

Episode 51 — Track AI Vulnerabilities: CVE Workflows, Advisories, and Exposure Management

Episode 50 — Use MITRE ATLAS Concepts for AI Threat Modeling and Adversary Behavior

Episode 49 — Apply OWASP Guidance to ML Risks: Abuse Patterns and Defensive Responses

Episode 48 — Apply OWASP Guidance to LLM Risks: Top Threats and Key Controls

Episode 47 — Operate Feedback Loops Safely: User Inputs, Reinforcement, and Toxic Drift

Episode 46 — Build Human Oversight That Works: Reviews, Approvals, and Accountability Points

Episode 45 — Plan Secure Maintenance: Patch Strategy, Versioning, and Rollback Discipline

Episode 44 — Control Model Exposure: Endpoints, APIs, Authentication, and Authorization Choices

Episode 43 — Design Secure Deployment Paths: Environments, Isolation, and Integration Boundaries

Episode 42 — Evaluate Models for Abuse: Misuse Paths, Safety Gaps, and Overreach Risks

Episode 41 — Select Models Securely: Capability Fit, Failure Modes, and Vendor Transparency

Episode 40 — Translate Requirements into Controls: Security, Privacy, and Reliability Criteria

Episode 39 — Anchor AI Security to Business Objectives: Use-Case Scope and Risk Appetite

Episode 38 — Enforce Data Access Boundaries: RBAC, ABAC, and Purpose-Based Controls

Episode 37 — Manage Data Retention: Deletion, Forgetting Limits, and Compliance-Driven Policies

Episode 36 — Encrypt AI Data Correctly: In Transit, At Rest, and In Use

Episode 35 — Protect Sensitive Data With Masking, Redaction, and Practical De-Identification

Episode 34 — Understand Watermarking Basics: Goals, Limits, and Validation Use Cases

Episode 33 — Preserve Integrity End-to-End: Hashing, Signing, and Controlled Transformations

Episode 32 — Build Lineage and Traceability: From Raw Sources to Model Artifacts

Episode 31 — Apply Data Augmentation Responsibly Without Introducing Backdoors or Skew

Episode 30 — Use Labeling Safely: Quality Controls, Annotation Bias, and Poisoning Exposure

Episode 29 — Apply Data Minimization: Collect Less, Store Less, and Expose Far Less

Episode 28 — Handle Structured, Semi-Structured, and Unstructured Data With Safe Controls

Episode 27 — Prevent Training Data Leakage: Secrets, PII, and Tokenization Side Effects

Episode 26 — Clean and Normalize Data Without Losing Security-Relevant Signal and Context

Episode 25 — Secure Data Intake: Authenticity Checks, Source Trust, and Provenance Tracking

Episode 24 — Manage Model Output Formats: Schemas, Parsing, and Safe Downstream Handling

Episode 23 — Calibrate Confidence Carefully: When to Trust Outputs and When to Escalate

Episode 22 — Reduce Hallucinations Practically: Grounding, Constraints, and Verification Patterns

Episode 21 — Separate System, Developer, and User Instructions to Prevent Confused Authority

Episode 20 — Control Tool Use in Agents: Permissions, Scope, and Safe Action Boundaries

Episode 19 — Write Prompt Templates That Reduce Variance and Prevent Risky Behaviors

Episode 18 — Use Zero-Shot, One-Shot, and Few-Shot Prompting With Clear Guardrails

Episode 17 — Build Prompt Foundations: Roles, Instructions, Context, and Output Constraints

Episode 16 — Choose Vector Stores Wisely: Indexing, Latency, Recall, and Access Controls

Episode 15 — Design Retrieval-Augmented Generation That Resists Abuse and Data Spillover

Episode 14 — Understand Embeddings Deeply: Similarity Search, Semantic Space, and Leakage Risks

Episode 13 — Apply Pruning and Quantization Without Breaking Security Expectations and Accuracy

Episode 12 — Fine-Tune Safely: Epochs, Learning Rates, and Catastrophic Forgetting Risks

Episode 11 — Explain Model Lifecycle States: Training, Tuning, Serving, and Retirement Criteria

Episode 10 — Validate Models Like a Defender: Cross-Validation, Holdouts, and Drift Awareness

Episode 9 — Spot Overfitting Early: Bias-Variance Tradeoffs and Generalization Failure

Episode 8 — Translate Model Metrics into Risk: Precision, Recall, F1, ROC, and Cost

Episode 7 — Compare Supervised, Unsupervised, and Reinforcement Learning for Security Use Cases

Episode 6 — Understand Transformers Clearly: Attention, Tokens, Context Windows, and Limits

Episode 5 — Explain Statistical Learning Foundations Security Pros Actually Use on the Job

Episode 4 — Map the AI Landscape for Security: ML, Deep Learning, and Generative Systems

Episode 3 — Lock In Exam-Day Tactics: Time, Stress, and Scenario Decision Patterns

Episode 2 — Build a Spoken Study Plan That Fits SecAI+ Objectives and Your Calendar

Episode 1 — Decode the SecAI+ Exam Blueprint, Scoring Rules, and Question Mechanics

Welcome to Certified: The CompTIA SecAI+ Audio Course