Turn cloud configuration evidence into prioritized findings and durable, policy-driven remediation across three providers
Establish a shared workload and evidence model for posture assessment across AWS, Azure, and Google Cloud.
Translate current CIS Foundations recommendations into comparable posture checks and remediation decisions across providers.
Explain how desired state, provider logs, identities, and delivery pipelines reveal unauthorized or unexpected changes.
Rank findings with data sensitivity, exposure, blast radius, and exploitability to create a reusable remediation rubric.
Use policy as code to prevent recurrence, verify corrections, and retire temporary exceptions through a controlled workflow.
3 sections · 6 lessons
Define a shared assessment boundary and evidence model, then connect CIS Foundations guidance to practical posture checks and remediation decisions across the three cloud providers.
2 lessonsRecognize recurring configuration weaknesses and examine how posture tools compare desired state with observed settings while tracing changes through provider records.
2 lessonsEvaluate findings with risk-based criteria, then build policy-as-code controls and a verification workflow that prevents recurrence and manages exceptions.
2 lessonsCloud security posture management requires consistent boundaries, evidence, and workload context across AWS, Azure, and Google Cloud. This course develops a vendor-neutral way to interpret CIS guidance, recognize risky configuration patterns, trace drift to identities and pipelines, and turn findings into prioritized remediation work. Learners leave with a reusable basis for assessing posture and applying policy-driven controls that prevent recurring misconfigurations.
The course covers shared CSPM scope and evidence, current CIS Foundations guidance, cross-cloud misconfiguration patterns, drift detection through provider logs, risk-based triage, service-level targets, and policy-as-code remediation workflows.
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Average pass rate · Freeman et al., PNAS 2014
What the science says
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You work through itAI does it for you
Skill retention over time · with vs. without practice
What the science says
Offloading thinking to AI erodes the very skills you’re trying to build.
How Fenzo does it
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Retrieval practiceRe-reading
Long-term recall · retrieval vs. re-reading
What the science says
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How Fenzo does it
Lessons weave in quizzes and recall prompts, so it sticks.