Episode 5 — Spot shared responsibility gaps that quietly create real cloud exposure
In this episode, we turn shared responsibility from an abstract idea into action steps you can actually verify, because the most common cloud exposures are not technical mysteries, they are ownership failures. When teams do not know who is responsible for which controls, they end up with invisible gaps where nobody is watching, configuring, or validating the settings that matter most. Shared responsibility is often explained as a diagram, but diagrams do not close incidents, and they do not prevent misconfiguration drift. What prevents exposure is a habit of translating responsibility into specific control outcomes, assigning owners, and collecting evidence that those outcomes are truly in place. If we do that well, you reduce the quiet kind of risk that accumulates over time and only becomes visible when something breaks or data leaks.
Before we continue, a quick note: this audio course is a companion to our course companion books. The first book is about the exam and provides detailed information on how to pass it best. The second book is a Kindle-only eBook that contains 1,000 flashcards that can be used on your mobile device or Kindle. Check them both out at Cyber Author dot me, in the Bare Metal Study Guides Series.
To define provider versus customer responsibilities clearly, start with concrete examples instead of slogans. The provider generally owns the security of the underlying facilities, hardware, core networking, and the foundational platform that runs the service. The customer owns the security of how the service is used, including identity permissions, data access boundaries, network exposure choices, and monitoring of activities within the customer’s environment. The dividing line shifts depending on the type of service, but the pattern stays the same: the provider secures the platform, and the customer secures their configuration and their data. For example, a provider may patch the managed database engine, but the customer still decides who can connect, whether the database is exposed publicly, what data is stored, and what logging is enabled. If you anchor your understanding in examples like that, it becomes harder to fall for the comforting belief that the provider has handled everything that feels complicated.
The dangerous assumption in cloud is not that someone else owns a control, it is the untested belief that someone else owns it. When people say someone else owns it, they often mean they do not want to think about it, or they assume the vendor has made a safe choice by default. That assumption becomes lethal when the control requires an explicit customer decision, such as enabling logging, constraining storage access, or narrowing identity permissions. It also becomes dangerous when responsibility is split, meaning the provider offers the capability but the customer must turn it on, configure it correctly, and then validate it continuously. In cloud environments, failure often looks like normal operation, so you cannot rely on intuition to detect gaps. You need ownership clarity and verification, because what is not owned is not maintained, and what is not maintained drifts into exposure.
Responsibility gaps show up most reliably in a few control areas, and you should treat these as your first places to look. Logging is a gap because providers may generate logs but customers often fail to centralize them, retain them, or alert on the right signals. Identity is a gap because permissions tend to be granted broadly early for speed and then never tightened, leaving roles and service identities with far more authority than needed. Storage access is a gap because storage services make sharing easy, and easy sharing creates accidental exposure when boundaries are assumed instead of tested. Patching is a gap because teams confuse provider patching of the underlying service with customer patching of applications, libraries, and configurations that sit on top of it. Each of these gaps creates real risk because each one is a force multiplier: weak logging delays detection, weak identity increases blast radius, weak storage access exposes data, and weak patching leaves exploitable weaknesses in place.
A scenario helps you see how these gaps play out even when a service is managed. Imagine a team adopts a managed storage or database service to reduce operational burden, and they interpret managed to mean secure. The provider does patching and infrastructure hardening, and the service stays highly available, so the team feels confident. Under deadline pressure, the team uses a quick setup option that enables broad access for testing, and they plan to restrict it later. That restriction never happens, or it happens only partially, and the service ends up storing sensitive data with access boundaries that are far wider than intended. No alerts fire because logging is not centralized and because access looks like legitimate use, and the exposure can persist quietly for months. The managed service reduced operational risk, but the shared responsibility gap created data exposure risk, and the incident was not caused by a platform failure, it was caused by ownership failure.
Default templates and setup wizards are a major pitfall because they feel like safe shortcuts. They often optimize for usability and getting to a working deployment quickly, and security-hardening is frequently presented as optional steps that can be added later. Under stress, later becomes never, and the template becomes the baseline for the environment. Templates can also hide the details that matter, such as which identity permissions were granted behind the scenes, what logging was enabled or disabled, and which network exposure choices were made for convenience. This is not a condemnation of templates, because they can be valuable when used carefully, but it is a reminder that templates are not policy. If a template produces a deployment, you still own the outcome, and you must verify the controls you care about rather than trusting the wizard’s implied safety.
A quick win that dramatically reduces shared responsibility gaps is to assign explicit owners for each control area, and to treat ownership as an operational duty, not a ceremonial title. Ownership means someone is accountable for the configuration state, the change process, and the evidence trail for that control. It also means someone is responsible for monitoring drift and responding when controls degrade. Without owners, controls exist only as intentions, and intentions do not survive organizational change, turnover, or competing priorities. With owners, controls gain continuity, because someone wakes up each week thinking about whether identity permissions are still tight, whether storage access is still bounded, and whether logs are still flowing. This single change often improves cloud security more than adding another tool, because it closes the human gap that tools cannot fix.
To make ownership meaningful, practice wording accountability questions that reveal gaps quickly without triggering defensiveness. You are not trying to accuse; you are trying to surface reality. A strong question asks who is responsible, what the expected control outcome is, how it is configured today, and how you know it is working. If nobody can answer who owns it, you found a gap. If someone answers but cannot describe how it is verified, you found a different gap. If a team says they think a provider handles it, you ask what evidence supports that belief. These questions work because they force responsibility claims to become operational claims, and operational claims can be tested. The tone matters, because calm curiosity gets better answers than confrontation, and the goal is to improve posture, not to win an argument.
Contracts and service tiers complicate shared responsibility, and you need to account for that because responsibility is not only technical, it is also legal and operational. Some service tiers include additional provider commitments, such as enhanced support, stronger uptime promises, or optional security features, but those features still usually require customer configuration. Contracts can also define how incidents are handled, what notifications occur, and what obligations exist for data handling and privacy. The key point is that contracts can shift expectations and provide additional mechanisms, but they rarely remove the customer’s need to configure identity, access, and monitoring correctly. Teams sometimes assume that paying for a higher tier automatically hardens security, and that is a misunderstanding that creates complacency. You want to interpret contracts as the boundaries of provider commitments, then layer your operational responsibilities on top, because your configuration choices remain the primary driver of exposure.
Evidence is what turns shared responsibility from a concept into a provable state, and evidence should be collectable without heroic effort. Evidence includes configuration records that show logging is enabled and exported to a central place, as well as retention settings that match your investigation needs. It includes identity permission reviews that show roles and service identities are scoped and that exceptions are tracked and justified. It includes storage access validation that demonstrates sensitive datasets are not publicly reachable and that access is limited to intended identities. It also includes patching and vulnerability management evidence for the parts you own, such as application dependencies and configuration baselines. Evidence should be current, because stale evidence creates false confidence. If you cannot collect evidence with reasonable effort, that is a signal that governance is too informal and needs structure.
A memory anchor helps you keep this work simple and continuous rather than episodic and reactive. The anchor for this episode is assign, configure, verify, and monitor continuously, and the sequence reflects what actually works. Assign means name an accountable owner for each control area and make that ownership operational. Configure means implement the control settings that produce the outcome you need, not the outcome the template happened to select. Verify means collect evidence that the control is operating as intended, including tests that prove access boundaries and logging flow. Monitor continuously means watch for drift, alerts, and changes, because cloud environments change constantly and yesterday’s secure configuration does not stay secure by accident. This anchor is powerful because it prevents a common failure mode where teams assign ownership but never verify, or configure controls but never monitor, leaving posture to decay quietly.
Now mini-review the common gaps and the questions that uncover them, because repetition builds faster recognition in real environments. For logging gaps, you ask where logs go, how long they are retained, and whether alerts exist for risky identity and exposure changes. For identity gaps, you ask who can change critical resources, how permissions are reviewed, and what prevents privilege creep in automation accounts. For storage access gaps, you ask what data is stored, who can access it, and how you test reachability and permission boundaries rather than assuming them. For patching gaps, you ask what the provider patches, what the customer patches, and how the customer proves patch status for applications and dependencies. The questions are effective because they force the team to separate belief from proof. Where proof is missing, exposure often follows.
Shared responsibility is not a one-time conversation because cloud environments evolve constantly, so commit to a cadence for revisiting responsibilities after changes. Every meaningful change introduces new services, new permissions, new data flows, and new exposure paths, and those changes can invalidate prior assumptions. A cadence is simply a routine schedule where owners re-check control outcomes, review evidence, and confirm that logging and monitoring still cover what matters. This is especially important after migrations, after major feature launches, after reorganizations, and after onboarding new teams. If you revisit only when an incident happens, you are learning at the most expensive time. When you revisit routinely, you catch drift early, when fixing it is cheaper and less disruptive. Cadence is what turns responsibility into a living practice rather than a document.
To conclude, choose one cloud service you know well and state responsibilities out loud as if you were teaching a new team member how to think about it. You describe what the provider owns at the platform layer and what you, as the customer, must configure and validate. You name the identity boundaries that must be set, the storage or data protections that must be enforced, and the logging signals that must be collected and monitored. You identify who owns each control area and what evidence proves it is operating today, not last quarter. Then you connect that back to the anchor assign, configure, verify, and monitor continuously, because that sequence is what keeps shared responsibility from turning into shared confusion. When you can narrate responsibilities this way, you are no longer relying on assumptions, and you are far less likely to be surprised by a cloud exposure that was quietly waiting for attention.
