AI Security Posture Management (AI-SPM) for Dummies
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After reading this guide, you’ll be able to:
Map every AI model, dataset, and pipeline step to a clear security-posture framework.
Spot and prioritize AI-specific threats such as prompt injection, data poisoning, and malicious models.
Build repeatable governance, monitoring, and response workflows that let teams innovate with confidence.
Key Takeaways
- Visibility before controlYou can’t secure AI systems you don’t know exist.
- Context drives prioritizationLinking cloud config, data flows, and model metadata reveals true attack paths.
- Governance enables innovationLightweight policy and automation keep guardrails in place without stifling speed.
Is this playbook for me?
This playbook is designed for:
Security architects and engineers charged with protecting AI workloads
Data-science and ML teams looking to “shift left” on risk and compliance
DevOps / platform teams integrating AI pipelines with existing cloud stacks
What’s included?
AI risk landscape primer – common and emerging threats, mapped to the OWASP GenAI Top 10.
AI-SPM building blocks – AI bill of materials (AI-BOM), data-security posture, and cross-cloud context.
Governance & policy templates – practical steps for visibility, access control, and change management.
Attack-path analysis workflow – how to trace, visualize, and remediate AI attack chains before they’re exploited.
Continuous improvement toolkit – metrics, drills, and feedback loops to keep security posture aligned with fast-moving AI projects.
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