Inferensys

Glossary

Confidential VM (CVM)

A Confidential VM (CVM) is a cloud virtual machine that utilizes hardware-based Trusted Execution Environments (TEEs) to encrypt its memory and vCPU state, protecting it from the hypervisor and other VMs on the same host.
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SECURE ENCLAVE EXECUTION

What is Confidential VM (CVM)?

A Confidential VM (CVM) is a cloud virtual machine that utilizes hardware-based Trusted Execution Environments (TEEs) to encrypt its memory and vCPU state, protecting it from the hypervisor and other VMs on the same host.

A Confidential VM (CVM) is a cloud virtual machine whose entire state—including memory, vCPU registers, and attached storage—is encrypted by the underlying processor using keys inaccessible to the hypervisor and cloud provider. This is achieved through hardware Trusted Execution Environments (TEEs) like AMD SEV-SNP or Intel TDX, which create a cryptographically isolated environment. The primary goal is to enforce confidential computing principles, ensuring data is processed in a manner where the host system cannot see or tamper with the workload, even if compromised.

This architecture fundamentally shifts the cloud security model by removing the hypervisor and host operating system from the Trusted Computing Base (TCB). Key features include memory encryption with integrity protection to prevent replay attacks and support for remote attestation, allowing clients to cryptographically verify the VM's integrity before deployment. CVMs are critical for securing sensitive AI agent tool execution, multi-tenant workloads, and regulated data processing in untrusted environments, providing a hardware-enforced alternative to software-only sandboxing.

CONFIDENTIAL VM (CVM)

Core Security Properties of a Confidential VM

A Confidential VM (CVM) leverages hardware-based Trusted Execution Environments (TEEs) to provide cryptographic isolation from the underlying cloud infrastructure. Its core security properties are defined by hardware-enforced guarantees.

01

Memory Encryption

A CVM's memory and vCPU state are encrypted with a key unique to the VM and generated by the hardware. This key is never accessible to the hypervisor or other VMs on the same physical host. This protects against:

  • Cold boot attacks on physical memory.
  • Hypervisor introspection or malicious administrators.
  • Adjacent VM attacks attempting to read memory via DMA (Direct Memory Access). Technologies like AMD SEV and Intel TDX implement this using an on-chip memory controller.
02

Attestable Integrity

The hardware provides a cryptographic measurement (hash) of the CVM's initial state, including its firmware, bootloader, and kernel. This measurement is signed by a hardware-rooted key. Through Remote Attestation, a remote client can verify:

  • The CVM is running on genuine, certified hardware with the correct security features enabled.
  • The initial software load is exactly the expected, unaltered version.
  • No unauthorized code has been injected prior to launch. This establishes a chain of trust from the silicon to the application.
03

Hypervisor Isolation

The hypervisor is removed from the Trusted Computing Base (TCB) for VM confidentiality. While it retains control for resource scheduling and device emulation, it cannot:

  • Read or modify the encrypted VM memory contents.
  • Inject code into the protected VM.
  • Access the VM's CPU register state during execution. This architectural shift is fundamental, transforming the hypervisor from a privileged controller to a distrusted manager of physical resources, drastically reducing the attack surface.
04

Secure I/O & Data-in-Use

CVMs extend protection to data during processing (data-in-use). For I/O operations, data must be decrypted for the CPU to process it, but this only happens within the secure CPU package. Technologies address the challenge of secure data ingress/egress:

  • Encrypted virtual disks: Data is encrypted with VM-specific keys before leaving the CVM's memory space for persistent storage.
  • Attested TLS: The CVM can prove its identity (via attestation) to external services to establish secure channels, ensuring data is only released to a verified, trusted environment.
05

Reduced Trusted Computing Base (TCB)

A key security goal is minimizing the Trusted Computing Base—the set of software/hardware that must be trusted for the system to be secure. In a traditional VM, the TCB includes the entire hypervisor and host OS (millions of lines of code). In a CVM, the TCB is reduced to:

  • The CPU's secure silicon and firmware (microcode).
  • The much smaller, auditable code running inside the CVM itself (e.g., the guest OS and application). This smaller TCB is easier to audit, verify, and reason about, leading to higher assurance.
06

Hardware Root of Trust

All CVM security properties are anchored in a Hardware Root of Trust. This is an immutable security engine within the processor that:

  • Generates and protects unique cryptographic keys.
  • Performs the initial integrity measurements for attestation.
  • Enforces the access policies for encrypted memory. It is physically part of the CPU silicon, making it extremely difficult to tamper with. This root of trust is what allows a remote party to have confidence in the CVM's reported security state, as it cannot be forged by software.
SECURE ENCLAVE EXECUTION

How Confidential VMs Work: The Technical Mechanism

A Confidential VM (CVM) is a cloud virtual machine that utilizes hardware-based Trusted Execution Environments (TEEs) to encrypt its memory and vCPU state, protecting it from the hypervisor and other VMs on the same host.

A Confidential Virtual Machine (CVM) leverages hardware Trusted Execution Environments (TEEs) like AMD SEV-SNP or Intel TDX to create an encrypted, hardware-isolated compute instance. The hypervisor provisions the VM but is cryptographically barred from accessing its memory or vCPU registers. Each CVM receives a unique, hardware-managed encryption key, ensuring its state is opaque to the host and any co-resident VMs, even if the hypervisor is compromised.

The security lifecycle begins with Remote Attestation, where the cloud provider's hardware cryptographically proves the CVM's integrity to the tenant before deployment. During operation, all memory pages and CPU register states are encrypted with the VM's key. This mechanism enforces a hardware-rooted chain of trust, shrinking the Trusted Computing Base (TCB) to exclude the hypervisor and host OS, thereby mitigating risks from insider threats and sophisticated side-channel attacks.

CONFIDENTIAL VM (CVM)

Frequently Asked Questions

Confidential VMs (CVMs) leverage hardware-based Trusted Execution Environments (TEEs) to create a secure, encrypted enclave for virtual machine execution in the cloud. These FAQs address their core mechanisms, security guarantees, and practical applications for isolating sensitive AI workloads.

A Confidential VM (CVM) is a cloud virtual machine that utilizes hardware-based Trusted Execution Environments (TEEs) to encrypt its memory and vCPU state, protecting it from the hypervisor and other VMs on the same host. It works by leveraging processor security extensions—such as AMD SEV, Intel TDX, or ARM CCA—to generate a unique, hardware-managed encryption key for each VM. This key is never exposed to the hypervisor or host operating system. All VM memory is encrypted on-the-fly as it leaves the CPU package, rendering it opaque to any other software, including a potentially compromised cloud provider stack. This creates an isolated execution environment where the VM's code and data are confidential and its integrity is verifiable via remote attestation.

Prasad Kumkar

About the author

Prasad Kumkar

CEO & MD, Inference Systems

Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.

His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.