Certified: The CompTIA SecAI+ Audio Course

Episoder

• Episode 90 — Prevent Shadow AI: Sanctioned Tools, Usage Rules, and Enforcement Patterns 22.02.2026 10min

   This episode focuses on preventing shadow AI as a governance and data protection requirement, because SecAI+ expects you to control unapproved tools that employees adopt for convenience, often without understanding how prompts, files, and proprietary data may be retained, reused, or exposed. You will learn why shadow AI emerges, including friction in approved tooling, unclear policies, and rapid feature availability, then connect that to practical risks like confidential data leaving the organization, licensing and IP exposure, inconsistent security logging, and uncontrolled model behaviors influencing decisions. We will cover prevention patterns such as providing sanctioned tools that meet real user needs, defining clear usage rules tied to data classification, implementing technical controls like access restrictions and DLP where appropriate, and creating training that explains what is allowed with concrete examples rather than vague warnings. You will also learn enforcement patterns that are realistic, including monitoring for risky data flows, investigating repeated violations, and adjusting policies and tooling to reduce incentives for workarounds, while keeping governance credible and auditable. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 89 — Apply Responsible AI Principles: Fairness, Transparency, and Explainability Choices 22.02.2026 11min

   This episode teaches responsible AI principles in an exam-ready, security-relevant way, because SecAI+ expects you to translate fairness, transparency, and explainability into practical choices that reduce harm, improve trust, and support governance rather than treating them as abstract ideals. You will learn how fairness concerns arise from biased data, uneven error rates across groups, and feedback loops that reinforce historical patterns, then connect those concerns to security outcomes like discriminatory access decisions, inconsistent fraud controls, or reputational risk after a public incident. We will cover transparency expectations such as clearly communicating system purpose, limitations, and data usage, and why transparency must be balanced against security needs so you do not reveal internal defenses or sensitive sources. You will also learn how to choose explainability methods that fit the model and the decision, including when simple interpretable models are preferable, when post-hoc explanations are acceptable with caveats, and how to validate that explanations are stable and not misleading. Troubleshooting considerations include detecting fairness regressions after retraining, documenting tradeoffs for auditors, and designing escalation rules so high-impact decisions always have human review and clear evidence trails. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 88 — Define AI Security Responsibilities: Owners, Approvers, Builders, and Auditors 22.02.2026 11min

  This episode focuses on defining responsibilities clearly, because SecAI+ scenarios often reveal failures caused by vague ownership, where everyone assumes someone else handled security review, data permissions, or monitoring, and the exam expects you to fix that with explicit accountability. You will learn how to separate responsibilities across owners who define outcomes and accept risk, approvers who validate security and compliance requirements, builders who implement controls and document evidence, and auditors who verify performance and investigate gaps independently. We will connect these roles to concrete artifacts like model cards and evaluation reports, data lineage documentation, access control decisions for retrieval and tools, change logs for prompts and model versions, and incident response playbooks for abuse, leakage, or drift. You will also learn how to avoid common pitfalls such as letting builders approve their own changes, leaving service accounts unmanaged, or assuming vendor attestations replace internal validation. Troubleshooting considerations include handling shared services across multiple business units, aligning responsibilities with existing security and compliance structures, and ensuring responsibilities remain valid as systems evolve from pilots to production services with real business impact. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 87 — Build AI Governance Structures: Policies, Roles, and a Working Operating Model 22.02.2026 10min

  This episode explains AI governance as an operating model that makes security and compliance achievable at scale, because SecAI+ expects you to choose governance structures that produce consistent decisions instead of one-off exceptions and informal approvals. You will learn what governance must cover, including approved use cases, data classification and access rules, model and vendor evaluation requirements, monitoring and incident response expectations, and change management for prompts, tools, and model versions. We will connect policies to roles and decision forums, showing why ownership must be explicit for model deployments, retrieval sources, tool permissions, and risk acceptance, and how a governance cadence prevents drift into unmanaged “pilot forever” systems. You will also learn how to make governance workable by defining lightweight intake processes, risk-tiering so low-risk use cases move quickly, and evidence requirements that scale, such as standard evaluation sets, documentation templates, and audit-ready logs. Troubleshooting considerations include avoiding governance that is so heavy it drives shadow AI, reconciling conflicting stakeholder priorities, and building escalation paths that resolve disputes while keeping risk decisions transparent and accountable. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 86 — Manage CI/CD With AI Assistants: Secure Pipelines, Tests, and Change Control 22.02.2026 11min

   This episode teaches how AI assistants fit into CI/CD without weakening security, because SecAI+ scenarios often involve AI-generated code, AI-suggested pipeline changes, or automated remediation that must still obey testing discipline and change control. You will learn where AI can help, such as drafting build steps, proposing tests, summarizing failures, and generating documentation, while emphasizing that pipeline integrity depends on controlled permissions, trusted runners, and tamper-resistant artifacts. We will connect secure pipelines to practical controls like signed commits and artifacts, protected branches, mandatory reviews for pipeline changes, secret scanning, and separation between build and deploy permissions so a compromised assistant or token cannot push directly to production. You will also cover how to treat AI-generated changes as untrusted until validated, including running unit, integration, and security tests, using SAST and dependency scans, and requiring evidence-based approvals for changes that affect authentication, data handling, or access control. Troubleshooting considerations include preventing an assistant from “fixing” failures by disabling checks, managing noisy test results without relaxing standards, and ensuring pipeline logs and outputs do not leak secrets through verbose debugging or AI summaries. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 85 — Apply Safe Automation: Low-Code Workflows With Guardrails and Auditability 22.02.2026 11min

   This episode focuses on safe automation using low-code workflows, because SecAI+ expects you to recognize that automation reduces toil but can also amplify errors and create new abuse paths when guardrails and auditability are weak. You will learn how low-code automations typically connect triggers, data sources, transformations, and actions, and why each step needs validation, authorization, and clear scope limits, especially when AI-generated content is involved. We will cover guardrails such as allowlisted actions, strict schema validation, approval gates for high-impact operations, and rate controls that prevent runaway loops and denial-of-wallet outcomes. You will also learn auditability requirements, including how to capture who initiated an automation, what data it accessed, what decisions were made, and what actions were executed, so incidents can be investigated without guesswork. Troubleshooting considerations include diagnosing failed automations that silently drop data, preventing brittle parsing from causing incorrect actions, and designing safe fallbacks that fail closed when inputs are missing, ambiguous, or untrusted. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 84 — Recognize AI-Assisted Malware Evolution: Obfuscation, Mutation, and Detection Gaps 22.02.2026 11min

  This episode teaches how AI can accelerate malware evolution by supporting rapid variation, improved obfuscation, and faster iteration on what evades detection, which is a key SecAI+ theme when scenarios ask you to respond to changing attacker capabilities without assuming perfect prevention. You will learn what mutation means in operational terms, including frequent changes to strings, structure, and delivery methods that break brittle signatures, and how obfuscation techniques can hide intent even when code is inspected superficially. We will connect these realities to detection gaps, explaining why static signatures alone degrade over time, why behavioral detection must be tuned carefully to avoid noise, and how attackers may test payload variants against common defensive tools to find the weakest points. You will also practice selecting best practices like layered detection, sandboxing and detonation where appropriate, strong endpoint hardening, rapid patching of common initial access paths, and robust telemetry that supports investigation even when the sample is unfamiliar. Troubleshooting considerations include validating whether an outbreak is truly “new malware” or simply a new wrapper, preventing analysts from over-trusting AI-generated family labels, and maintaining disciplined response steps that are grounded in observed behavior and evidence. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 83 — Track AI-Accelerated Recon: Target Discovery, Enumeration, and Defensive Signals 22.02.2026 12min

   This episode focuses on how AI accelerates reconnaissance by reducing attacker effort in discovering targets, mapping organizations, and enumerating exposed systems, and how SecAI+ expects you to translate that reality into defensive monitoring and hardening choices. You will learn what recon looks like in practice, including automated collection of public-facing assets, rapid analysis of job postings and org charts for tech stacks, large-scale scanning for misconfigurations, and content harvesting that supports tailored pretexts. We will connect these behaviors to defensive signals such as unusual crawling patterns, spikes in 404 and authentication failures, anomalous queries against public APIs, and repeated access attempts across subdomains and endpoints that suggest systematic enumeration. You will also practice selecting controls like tightening external exposure, enforcing consistent authentication, reducing information leakage in public repositories and documentation, and improving alerting so recon activity is visible before it turns into exploitation. Troubleshooting considerations include distinguishing legitimate scanners and partners from adversarial probing, tuning rate limits without breaking normal traffic, and using threat intel context to prioritize which exposure reductions deliver the most risk reduction. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 82 — Counter AI-Scaled Social Engineering: Phishing, Vishing, and Pretext Detection 22.02.2026 13min

   This episode teaches how AI scales social engineering by making messages more convincing, more personalized, and easier to generate at volume, which is exactly why SecAI+ includes scenarios that test your ability to spot and disrupt pretexts rather than simply telling users to “be careful.” You will connect AI-scaled phishing and vishing to practical indicators like timing, unusual requests, urgency cues, and mismatches between the request and normal business process, then shift to controls that reduce success even when a message is persuasive. We will cover process countermeasures such as verified call-back procedures, approval chains for payment and access changes, identity-aware authentication that does not depend on what someone says, and mailbox protections that reduce spoofing and malicious link delivery. You will also learn how to detect campaign patterns through telemetry, including spikes in lookalike domains, repeated themes across departments, and abnormal helpdesk requests, and how to respond with containment steps that preserve evidence while cutting off attacker momentum. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 81 — Understand AI-Driven Deepfakes: Impersonation Risk and Verification Countermeasures 22.02.2026 14min

   This episode explains why AI-driven deepfakes are a security problem, not just a media curiosity, and how SecAI+ expects you to analyze impersonation risk in realistic organizational workflows. You will define deepfakes across audio, video, and synthetic identity artifacts, then connect them to attack paths like executive impersonation for wire fraud, fake candidate interviews, synthetic support calls to reset credentials, and manipulated evidence in incident narratives. We will focus on verification countermeasures that actually hold up under pressure, including out-of-band verification, shared secrets that are not guessable from public data, identity proofing steps that do not rely on a single channel, and policy-driven controls that require secondary approvals for high-impact actions. You will also learn defensive signals and troubleshooting considerations, such as why “spot the artifact” is unreliable, how to design business processes that assume deception is possible, and how to train teams to verify intent and authorization rather than arguing about whether the voice sounded real. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 80 — Use AI for Threat Intel: Entity Extraction, Clustering, and Confidence Handling 22.02.2026 13min

  This episode teaches practical uses of AI in threat intelligence, because SecAI+ expects you to apply AI to messy text and indicator data while still handling uncertainty, provenance, and bias responsibly. You will learn how AI can extract entities such as malware names, CVEs, infrastructure, and actor references from reports, cluster similar narratives to identify campaigns, and summarize key takeaways for analysts and leaders, while recognizing that source quality and model hallucination risk can distort conclusions. We will connect these capabilities to confidence handling, showing why intel should be tagged with confidence levels, linked to sources, and cross-checked against internal telemetry and trusted feeds before driving security actions. You will also learn how to prevent common errors like conflating similarly named actors, over-trusting unverified indicators, or allowing AI-generated summaries to strip out critical caveats and timelines that change meaning. Troubleshooting considerations include managing duplicates across feeds, improving clustering quality without leaking sensitive internal data, and building workflows where AI accelerates intel processing while humans retain responsibility for validation and decision-making. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 79 — Use AI for Incident Triage: Summaries, Prioritization, and Evidence Integrity 22.02.2026 13min

  This episode focuses on using AI for incident triage without compromising evidence integrity, because SecAI+ expects you to accelerate understanding while still preserving the chain of custody and avoiding premature conclusions driven by fluent summaries. You will learn how AI can summarize alerts, cluster related events, extract key entities like hosts and accounts, and propose prioritization based on impact indicators, while emphasizing that these outputs must be grounded in logs and artifacts rather than treated as authoritative conclusions. We will cover safe triage workflows such as requiring citations to specific evidence fields, using structured outputs that separate facts from hypotheses, and escalating to human review when the incident involves sensitive systems, potential data exposure, or high business impact. You will also learn how to protect evidence by controlling what data is sent to AI services, redacting sensitive fields where possible, and logging AI-assisted decisions for later review. Troubleshooting considerations include detecting when summaries omit critical context due to truncation, preventing the model from smoothing over uncertainty, and ensuring that triage acceleration does not cause analysts to skip essential validation steps that would matter during post-incident reporting. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 78 — Use AI for Detection Engineering: Rules, Correlation, and Noise Reduction 22.02.2026 14min

  This episode teaches AI-assisted detection engineering in a way that matches SecAI+ expectations, because exam scenarios often involve improving detection coverage and quality while controlling false positives, preserving evidence, and avoiding overfitting detections to yesterday’s attacks. You will learn how AI can help draft detection rules, suggest correlations across logs, and propose enrichment logic that makes alerts more actionable, while still requiring defenders to validate assumptions about environment, telemetry quality, and attacker behavior. We will cover noise reduction strategies such as normalizing event fields, grouping similar alerts, tuning thresholds with cost awareness, and building suppression rules that are evidence-based rather than convenience-based. You will also learn how to keep detection engineering resilient by testing rules against baselines, simulating common attacker techniques, and monitoring for drift as systems and behaviors change. Troubleshooting considerations include diagnosing why correlations break when logs are missing or inconsistent, preventing AI from inventing fields your telemetry does not actually capture, and ensuring rule changes follow change control and are auditable for incident response and continuous improvement. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 77 — Use AI for Code Review: Linting, SAST Triage, and False-Positive Control 22.02.2026 13min

  This episode focuses on using AI to improve code review efficiency without weakening security rigor, because SecAI+ expects you to balance speed gains against the risk of missed findings, noisy recommendations, and overconfident summaries that hide uncertainty. You will learn how AI can assist with linting and style consistency, explain SAST findings in clearer language, and help triage false positives by mapping findings to code context, data flow, and intended behavior. We will also cover the pitfalls, including hallucinated vulnerability explanations, shallow pattern matching that misses business-logic flaws, and suggestions that “fix” a warning by suppressing it rather than addressing the underlying risk. You will practice selecting safe workflows, such as using AI to propose hypotheses while requiring reviewers to confirm with source code and tests, enforcing structured outputs that link claims to specific lines and evidence, and tracking reviewer feedback to improve prompts and triage rules over time. Troubleshooting considerations include calibrating AI assistance so it reduces workload instead of increasing debate, preventing sensitive code leakage into external services, and documenting decisions so audits can see why a finding was accepted, rejected, or deferred. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 76 — Use AI in Secure Coding: Generating Code Without Injecting Vulnerabilities 22.02.2026 13min

  This episode teaches how to use AI for code generation without turning your SDLC into a vulnerability factory, because SecAI+ expects you to recognize that AI can accelerate delivery while also increasing risk if outputs are trusted blindly. You will learn common failure modes in generated code, such as insecure defaults, weak input validation, unsafe deserialization, improper authentication and authorization checks, and fragile error handling that leaks sensitive details. We will connect these risks to practical controls like requiring secure coding standards in prompts and templates, constraining output formats, banning certain risky patterns unless explicitly justified, and validating outputs with testing and scanning before merge. You will also learn how to handle dependency risks when AI suggests libraries or snippets copied from unknown sources, including license and provenance concerns, and why secrets must never be embedded in generated examples. Troubleshooting considerations include dealing with subtle logic flaws that pass compilation but fail security expectations, designing review checklists that catch recurring AI mistakes, and setting up guardrails so code generation is helpful while still operating inside clear policy boundaries. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 75 — Reduce Overreliance Risk: Human Verification Loops and Safe Escalation Rules 22.02.2026 13min

  This episode focuses on overreliance as a real operational hazard, because SecAI+ expects you to design workflows that keep humans in control of high-impact decisions even when AI outputs are fluent, fast, and usually correct. You will learn why overreliance happens, including automation bias, time pressure, and unclear accountability, and how it leads to failures like approving unsafe changes, misclassifying incidents, or repeating incorrect claims in official communications. We will cover human verification loops that actually work, including risk-tiering of tasks, structured outputs that make review faster, sampling strategies that avoid review fatigue, and escalation rules that trigger mandatory human involvement when inputs are sensitive, evidence is missing, or the action would change access, money, or safety outcomes. You will also learn how to define safe escalation paths so “I’m not sure” becomes a controlled handoff rather than a hidden failure, and how to measure whether oversight is effective using error trends, reversal rates, and audit outcomes. Troubleshooting considerations include preventing rubber-stamp reviews, avoiding bottlenecks that teams bypass, and aligning oversight design with organizational risk appetite and compliance expectations. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 74 — Secure Integrations and Plug-Ins: Trust Boundaries, Validation, and Least Privilege 22.02.2026 14min

  This episode teaches integration security for AI systems, because SecAI+ scenarios often involve plug-ins, connectors, and third-party services that expand capability while also expanding attack surface and data exposure pathways. You will learn how to define trust boundaries between the model, the orchestration layer, external plug-ins, and internal systems of record, and why untrusted integration outputs must be treated as data to validate, not instructions to follow. We will cover validation and sanitization at integration points, including schema enforcement, strict allowlists for actions, and defensive handling of malformed or adversarial responses that try to manipulate the model’s behavior. You will also learn least-privilege patterns for integrations, such as scoped tokens, minimal permissions, environment segmentation, and human approval gates for high-impact actions, along with audit trails that capture what was requested, what was returned, and what was executed. Troubleshooting considerations include diagnosing over-permissioned connectors, preventing data spillover across tenants, and ensuring plug-in failures degrade safely without prompting the agent to improvise risky workarounds. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 73 — Handle Denial-of-Service Risks: Model DoS, Cost Bombs, and Resilience 22.02.2026 14min

  This episode focuses on denial-of-service in AI systems, because SecAI+ expects you to defend not only availability, but also cost stability and operational continuity when models can be abused with oversized prompts, pathological inputs, or tool chains that amplify resource use. You will learn how model DoS differs from traditional API DoS, including token-based cost bombs, long-context payloads that spike compute and latency, and prompt patterns designed to trigger expensive retrieval or repeated tool calls. We will cover resilience strategies such as strict input length limits, rate limiting by identity and tenant, request prioritization, circuit breakers for tool chains, and caching where appropriate to reduce repeated heavy work. You will also learn how to monitor for early signals like sudden token consumption spikes, abnormal latency distributions, and correlated tool invocation storms, then respond with containment actions that isolate abusive clients without collapsing service for everyone. Troubleshooting topics include balancing availability protections with usability, preventing attackers from learning your thresholds through verbose errors, and designing graceful degradation modes that preserve safe core functionality under load. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 72 — Prevent Model Theft: Extraction Risks, Query Limits, and Watermark Strategies 22.02.2026 14min

  This episode teaches model theft as an access and abuse problem, because SecAI+ scenarios often involve attackers trying to replicate a model’s behavior by querying it repeatedly, capturing outputs, and building a substitute that steals value and may later be used for harmful activity. You will learn how extraction attempts typically present, including high-volume, systematically varied prompts, probing for decision boundaries, and targeted requests that map the model’s behavior across topics and formats. We will connect extraction risk to practical defenses such as strong authentication, tiered entitlements, rate limiting and quotas, anomaly detection for suspicious request patterns, and response shaping that avoids unnecessary detail while still meeting business needs. You will also learn how watermark strategies may be used to support provenance and investigation in some contexts, while understanding their limits and why they do not replace access control and monitoring. Troubleshooting considerations include tuning limits to protect legitimate power users, detecting slow-and-steady extraction campaigns, and designing incident response playbooks that include throttling, token rotation, and evidence preservation. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
• Episode 71 — Analyze Membership Inference Risks: Privacy Exposure and Defensive Techniques 22.02.2026 15min

  This episode focuses on membership inference as a practical privacy risk, because SecAI+ expects you to recognize when attackers can probe a model to determine whether a specific record was part of its training data and why that matters for confidentiality and compliance. You will learn how membership inference typically works, including repeated querying, confidence score analysis, and comparison across similar inputs to detect “training set familiarity,” and why models can leak this signal even when they never output the original record directly. We will connect the risk to real scenarios such as customer data in fine-tuning sets, internal incident narratives used for training, or proprietary documents embedded into evaluation corpora, then discuss defensive techniques like data minimization, careful train-test separation, privacy-aware training approaches where appropriate, output constraints that avoid overly specific responses, and rate limiting that reduces an attacker’s ability to iterate. You will also cover monitoring and investigation steps that help you detect probing behavior and respond with containment, evidence capture, and retraining or policy updates when exposure is suspected. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.