Confidential Container

The container runtime leverages CPU-level memory encryption engines to automatically encrypt all data in use. Unlike standard containers that share memory with the host OS, Confidential Containers ensure that even a compromised hypervisor or root user cannot read plaintext memory pages. Technologies like AMD SEV-SNP and Intel TDX provide per-VM or per-enclave encryption keys managed by the processor's security processor, not the operating system.

Standard containers share the host operating system kernel, creating a large attack surface. Confidential Containers remove the host kernel from the Trusted Computing Base (TCB). The workload runs in an encrypted memory region where the host can only see encrypted pages. This protects against:

• Container escape vulnerabilities in the host kernel
• Malicious infrastructure administrators with root access
• Memory scraping attacks from co-located tenants

Before a Confidential Container receives sensitive data or secrets, it must prove its identity and integrity through remote attestation. The hardware generates a cryptographically signed report containing the container's measurement—a hash of its initial code, configuration, and firmware. An Attestation Service verifies this report against known good values. Only after successful verification are decryption keys released, ensuring the workload is exactly what it claims to be.

Unlike early enclave technologies that required application rewrites, modern Confidential Container runtimes support standard OCI images. Projects like Kata Containers with Confidential Computing extensions run unmodified container images inside hardware-isolated VMs. The guest kernel and root filesystem are measured and attested, but the application layer remains unchanged. This preserves developer workflows while adding hardware-grade isolation.

When a Confidential Container writes data to disk, it uses enclave sealing to encrypt the data before it leaves the TEE boundary. The encryption key is derived from the enclave's unique identity and the platform's hardware root of trust. This means:

• Data at rest is bound to a specific container identity
• Stolen disks or storage snapshots cannot be decrypted
• Data can only be unsealed by the same application on the same or attested platform

Confidential Containers integrate with service mesh technologies to extend protection to network communication. Mutual TLS sessions are established using attested identities rather than just network credentials. Each sidecar proxy runs within the TEE boundary, ensuring that traffic decryption happens inside protected memory. This creates a Confidential Service Mesh where data remains encrypted across the entire request path—from ingress to application logic to egress.

Run sensitive AI inference workloads in a public cloud while cryptographically denying the cloud provider access to data in use. The container runtime launches inside a Confidential VM (CVM) backed by AMD SEV-SNP or Intel TDX, encrypting all memory pages.

• Use case: A SaaS company processes proprietary client documents using a self-hosted LLM without exposing prompts to the hypervisor.
• Mechanism: The Kata Containers runtime creates a lightweight VM per pod, isolating the guest kernel from the host.
• Attestation flow: Before pulling model weights, the container performs remote attestation against an Enclave-Aware Key Management Service to prove its identity.

Deploy a Confidential Container as the central aggregation server in a Federated Learning topology. Model updates from edge devices are decrypted and averaged entirely within a Trusted Execution Environment, ensuring the aggregator operator cannot inspect individual contributions.

• Key property: The aggregation logic and in-memory gradient buffers are encrypted by the hardware, preventing introspection by the infrastructure owner.
• Attestation requirement: Edge clients verify the container's enclave measurement before transmitting encrypted weight deltas.
• Benefit: Satisfies data residency and privacy regulations in healthcare and finance consortia.

Execute the entire Retrieval-Augmented Generation stack inside a Confidential Container to protect both the proprietary knowledge base and the user's query. The vector search and LLM inference run in a single Intel SGX or AMD SEV-SNP enclave.

• Data-in-use protection: The retrieved document chunks and the generated response remain encrypted in DRAM, invisible to the cloud operator.
• Secure indexing: The vector database runs within the same TEE boundary, sealing its index to the enclave identity for persistent storage.
• Attestation chain: The client verifies the container's model provenance attestation to confirm the exact LLM binary and knowledge base hash before sending a query.

Deploy Confidential Containers in a physically disconnected on-premises GPU cluster to serve proprietary foundation models. The TEE ensures that even local administrators with root access cannot extract model weights from memory.

• Hardware: NVIDIA Confidential Computing with H100 GPUs creates an isolated execution environment where model parameters are encrypted during inference.
• Secure GPU Attestation: The orchestrator verifies the GPU firmware and driver integrity before scheduling the confidential workload.
• Operational model: The container's Trusted Computing Base (TCB) is limited to the CPU, GPU, and the minimal guest kernel, excluding the host OS and hypervisor.

Integrate Confidential Containers into a Zero-Trust AI Networking architecture where every inter-service call is mutually attested. Sidecar proxies run inside the TEE boundary, ensuring that data remains encrypted during transit between microservices.

• Identity: Each container obtains a cryptographic identity via SPIRE, attested against the hardware root of trust.
• Policy enforcement: The mesh enforces that only attested enclaves with specific measurements can communicate, preventing lateral movement.
• Use case: A multi-stage AI pipeline where a data preprocessing container feeds a confidential inference container, with all intermediate data protected.

Maintain workload continuity during infrastructure maintenance by migrating a running Confidential Container between physical hosts without exposing plaintext memory. The AMD SEV-SNP and Intel TDX extensions support secure live migration.

• Migration flow: The source platform encrypts the VM state with a transport key, transfers it, and the destination platform re-encrypts it with a new memory encryption key.
• Attestation continuity: The destination platform must provide a fresh attestation report proving its TEE integrity before the migration completes.
• Benefit: Enables high-availability confidential workloads in dynamic cloud environments without violating the security model.