Building AI Security Together: New Ways to Partner with Wiz for AI Security in 2026
Enhancing the Wiz Integration Network with a new WIN MCP, developer AI agent, WIN AI security category, and partner AI hackathon
This cheat sheet is designed for:
Cloud Security Engineers: Implement robust network boundaries, encryption standards, and identity guardrails specifically tuned for Vertex AI workloads.
DevSecOps & MLOps Professionals: Automate security within CI/CD pipelines to ensure only verified, scanned, and authorized models reach production.
AI/ML Architects & Data Scientists: Build and deploy models on a secure-by-design foundation without sacrificing the speed of innovation on Google Cloud.
Security Leaders & IT Managers: Use a practical roadmap to strengthen AI governance, reduce organizational risk, and manage the "Shared Responsibility" model.
Compliance & Audit Teams: Improve visibility through immutable audit logging and data residency controls to support regulatory reporting and investigation readiness.
What’s included?
Identity & Access Management: Deep dive into roles, service account hardening, and Workload Identity Federation for AI workloads.
CI/CD & Pipeline Integrity: Controls for scanning third-party dependencies, tracking artifact lineage, and enforcing approved pipeline templates.
Infrastructure & Network Security: How to use VPC Service Controls and Private Service Connect to create a "zero-trust" environment for AI.
Generative AI Safety & Red Teaming: Strategies for testing model resilience and configuring filters for the Gemini model family.
Threat Detection & Incident Response: Leveraging Model Armor and Event Threat Detection to identify and remediate active security incidents in real-time.
Enhancing the Wiz Integration Network with a new WIN MCP, developer AI agent, WIN AI security category, and partner AI hackathon
Wiz protects AI infrastructure against cloud attacks, allowing data scientists and engineers to focus on deploying more AI applications.
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