Mastering NIST SSDF for Generative AI: Accelerate Secure Agent Development with Step-by-Step Frameworks and Automation (Software Engineering, Cloud Architecture & AI Governance)

Greer, Tyrell T.

ISBN 13: 9798299394955

Verlag: Independently published, 2025

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Bibliografische Details

• Titel: Mastering NIST SSDF for Generative AI: Accelerate Secure Agent Development with Step-by-Step Frameworks and Automation (Software Engineering, Cloud Architecture & AI Governance)
• Verlag: Independently published
• Erscheinungsjahr: 2025
• Sprache: Englisch
• ISBN-13: 9798299394955
• Einband: Softcover
• Zustand: New

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Inhaltsangabe

Mastering NIST SSDF for Generative AI: Accelerate Secure Agent Development with Step-by-Step Frameworks and Automation

What’s holding back your next generative AI project—the power of your models, or your confidence that what you build is truly secure? As the pace of AI innovation surges, security blind spots can turn rapid progress into unexpected setbacks. Teams often find themselves patching vulnerabilities late, scrambling after a compliance scare, or struggling to prove their models are safe, reliable, and audit-ready. But it doesn’t have to be this way.

This practical, no-nonsense guide delivers what AI and security engineers need most: a hands-on, workflow-driven approach to embedding NIST’s Secure Software Development Framework (SSDF) into every phase of generative AI agent development. You’ll move beyond scattered advice and generic checklists, learning instead how to apply proven automation and control techniques that have been tested on the front lines of real-world AI deployments.

Inside, you’ll discover how to:

• Establish security governance that scales with your team and automates policy enforcement using CI/CD pipelines, versioned policies, and role-based access control.

• Protect your AI assets by validating data provenance, automating dependency tracking with SBOMs, and implementing model artifact signing to prevent tampering.

• Bake security into every build with coding patterns, automated SAST/DAST/fuzzing, and continuous integration gates that keep threats out of production.

• Automate security across your entire development and deployment pipeline—using detailed scripts, templates, and ready-to-implement YAML examples for Jenkins, GitHub Actions, and GitLab CI.

• Respond rapidly to AI-specific security incidents with monitoring, anomaly detection, rollback strategies, and incident response templates tailored for generative models.

• Align your processes with industry frameworks like OWASP SAMM, BSIMM, and ISO 27034 using mapping matrices and actionable compliance dashboards.

This book arms you with code you can run, playbooks you can trust, and strategies you can immediately apply—whether you’re launching your first secure AI agent or tightening controls across a mature multi-model platform. With each recipe, you’ll gain the practical skills to transform security from a blocker into a competitive advantage for your AI teams.

Ready to build generative AI agents that are not just innovative, but resilient, auditable, and production-grade? Take the next step—add “Mastering NIST SSDF for Generative AI” to your toolkit and lead your organization into the future of secure, scalable, and trustworthy AI development.