Aviatrix Zero Trust for AI Workloads: Default-Deny AI Governance at the Network Layer

What's inside the solution brief:

• Why AI gateways, detection tools, and application-layer controls have a structural blind spot — and why the network layer is the only enforcement point that sees every LLM call, RAG pipeline, and MCP server communication regardless of how it's routed

• How AI WebGroups provide Aviatrix-managed, auto-updated containment boundaries for every major LLM provider, vector database, MCP gateway, and agent framework — so your policies stay current without a ticket when providers rotate IPs or launch new model APIs

• How SmartGroups resolve workload identity from Kubernetes pod labels, AWS/Azure/GCP cloud tags, Lambda ARNs, and Bedrock Agent definitions — so containment policy follows the workload, not a fragile IP address

• How the Distributed Cloud Firewall enforces default-deny at the VPC boundary where Kubernetes egress actually happens — not at a centralized proxy that containers can bypass

• How a financial services firm enforced production-to-Bedrock-only and dev-to-any-approved-LLM with two DCF rules and two SmartGroup tags — containing shadow AI before it reached anything sensitive, with no developer tooling changes

• How the same containment architecture stopped The Cascade, the March 2026 Trust Chain attack, at a Fortune Global 500 — zero credentials exfiltrated, four IP addresses, one engineer

• How to generate continuous, audit-ready AI egress evidence for EU AI Act compliance — every egress decision attributable to a SmartGroup, WebGroup, and DCF rule, covering LLM apps, RAG pipelines, and agentic workloads equally