Follow a step-by-step guide to perform confidential compute attestation on io.net Cloud provisioned VMs. Verify NVIDIA GPUs, validate cryptographic proofs, and ensure trusted execution for secure workloads.
This guide shows you how to perform GPU attestation and verification on Virtual Machines provisioned by io.net Cloud, this allows you to verify NVIDIA GPUs and validate cryptographic evidence to ensure workloads run in a Trusted Execution Environment (TEE).
Before running GPU verification for the first time, you need to install NVIDIA’s official attestation tools. This setup takes about 2–3 minutes and only needs to be completed once per VM.
1
Connect to your VM
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ssh root@your-vm-ip
2
Create Verification Directory
Create a dedicated directory to store the verification tools and scripts.
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mkdir -p ~/gpu-verificationcd ~/gpu-verification
3
Create a Python Virtual Environment
Use a virtual environment to keep dependencies isolated and avoid conflicts with system packages.
This verification process will take approximately 30 seconds.
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# Connect to your virtual machinessh root@your-vm-ip# Navigate to the verification directorycd ~/gpu-verification# Activate the Python virtual environmentsource venv/bin/activate# Run the verification scriptpython3 verify_gpu.py
The verification script performs the following steps automatically:
1
Generating a Cryptographic Nonce
Creates a random 32-byte challenge value.
Ensures attestation freshness and prevents replay attacks.
2
Collecting Evidence from GPUs
Queries each GPU for attestation evidence (typically takes approximately 20 seconds).
Retrieves certificate chains directly from the GPU hardware.
Collects firmware measurements for both the driver and VBIOS.
Gathers all required cryptographic signatures.
3
Validating Attestation Evidence
Verifies that certificate chains trace back to the NVIDIA Root Certificate Authority.
Checks certificate revocation status using OCSP (Online Certificate Status Protocol).
Retrieves Reference Integrity Manifests (RIMs) from NVIDIA.
Compares runtime firmware measurements against known golden RIM values.
Validates all cryptographic signatures to ensure integrity and authenticity.
Expected Output (Success)
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======================================================================NVIDIA GPU Confidential Compute VerificationUsing official NVIDIA nv-attestation-sdk======================================================================[1/3] Generating cryptographic nonce... Nonce: 6040f42cc179...[2/3] Collecting evidence from GPUs... This may take 20-30 seconds... Found 8 GPU(s) with CC support[3/3] Validating attestation evidence... • Verifying certificate chains • Checking OCSP revocation status • Validating firmware measurements (RIM) • Verifying cryptographic signatures======================================================================✅ VERIFICATION SUCCESSFUL======================================================================This system has 8 genuine NVIDIA GPU(s)with Confidential Computing features enabled and operational.Verification completed: ✅ Certificate chains are valid ✅ Certificates are not revoked (OCSP) ✅ Firmware measurements match golden RIM values ✅ Hardware attestation passed======================================================================
Contact support immediately if any of the following messages appear:
❌ “VERIFICATION FAILED”
❌ “Certificate validation failed”
❌ “RIM verification failed”
❌ “OCSP check failed (revoked)”
❌ “No GPUs with Confidential Computing support found”
What this may indicate:
The hardware does not support Confidential Computing.
The system is misconfigured.
Network connectivity issues are preventing access to OCSP or RIM services.
A potential security issue that requires further investigation.
Do not process sensitive or confidential data if verification fails.All failures should be investigated and resolved before running protected workloads.
This section outlines common issues encountered during GPU attestation and provides guidance on how to diagnose and resolve them.
Issue: "No GPUs with Confidential Computing Support Found"
Possible causes:
The virtual machine type does not support Confidential Computing.
NVIDIA drivers are not installed or are not properly loaded.
Confidential Computing features are not enabled at the BIOS or firmware level.
Verify GPU presence:
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nvidia-smi
Expected result:
The output should list NVIDIA H100 or H200 GPUs.If no GPUs are shown:
Contact support, as the virtual machine may not be provisioned with the correct hardware.
Issue: Network Timeouts or Connection Errors
Possible causes:
Firewall rules blocking outbound HTTPS traffic to NVIDIA services.
No internet connectivity from the virtual machine.
Temporary unavailability of NVIDIA attestation services.
Test connectivity to NVIDIA services:
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# Test NVIDIA OCSP servercurl -v https://ocsp.nvidia.com# Test NVIDIA RIM servicecurl -v https://rim.attestation.nvidia.com
If access is blocked:
Update firewall rules to allow outbound HTTPS traffic (port 443) to the following endpoints:
ocsp.nvidia.com
rim.attestation.nvidia.com
Issue: Verification Takes Longer Than Expected
Normal execution time:
First run: 45–60 seconds (initial download of RIM files)
Subsequent runs: 30–45 seconds (cached RIM files are reused)
If execution exceeds five minutes:
Network latency may be affecting access to NVIDIA services.
Cancel the process using Ctrl + C and retry.
If the issue persists, contact support for further assistance.
Issue: “ModuleNotFoundError” or Import Errors
Possible cause:
The Python virtual environment is not activated.Solution:
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cd ~/gpu-verificationsource venv/bin/activate # (venv) should appear in the promptpython3 verify_gpu.py
Issue: Package Installation Fails
Possible causes:
No internet connectivity during setup.
Inability to reach the PyPI repository.
Insufficient available disk space.
Solution:
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# Verify internet connectivityping -c 3 pypi.org# Check available disk spacedf -h# Retry installationcd ~/gpu-verificationsource venv/bin/activatepip install --upgrade pippip install nv-attestation-sdk