FAQ: Is io.net Secure for Enterprise Workloads?

Quick Answer

Yes, io.net is secure for enterprise workloads with Confidential Compute for data encryption during processing, SOC 2 Type II certification in progress (expected Q3 2026), private networking, encrypted storage, and enterprise-grade security controls. While io.net's decentralized model initially raises questions about data security on third-party GPUs, the platform's Confidential Compute feature uses Trusted Execution Environments (TEEs) to ensure GPU providers cannot access your data, code, or model weights. Companies including Render Network, OpenGPU, and several Fortune 500 AI teams (under NDA) run production workloads on io.net. For maximum security, enable Confidential Compute ($0.20/hr premium per GPU) which provides hardware-level encryption equivalent to AWS Nitro Enclaves or Azure Confidential Computing.

Enterprise Security Features

Confidential Compute (Hardware-Level Encryption)
- Technology: AMD SEV-SNP or Intel TDX Trusted Execution Environments
- Protection: Encrypts data in GPU memory - providers cannot access your data
- Use case: Sensitive datasets, proprietary models, HIPAA/PCI-DSS compliance
- Availability: H100, A100 GPUs with TEE support
- Cost: +$0.20/hr per GPU premium
- Status: Generally available (GA) as of March 2026

Private Networking
- Isolated VPCs: Private network per customer (no shared networking)
- Encrypted traffic: TLS 1.3 for all data in transit
- SSH tunneling: Secure access to GPUs without public IPs
- VPN integration: Connect io.net GPUs to your corporate VPN
- Firewall rules: Whitelist only your IP addresses

Encrypted Storage
- At-rest encryption: AES-256 encryption for all persistent volumes
- Key management: Bring Your Own Key (BYOK) support for enterprise
- Secure deletion: Cryptographic erasure on volume deletion
- Immutable backups: Point-in-time snapshots with retention policies

Access Controls
- SSO integration: Okta, Azure AD, Google Workspace
- Role-Based Access Control (RBAC): Team admin, developer, billing roles
- 2FA enforcement: Mandatory for enterprise accounts
- API key rotation: Automatic 90-day rotation
- Audit logs: 90-day retention of all API calls, GPU access, billing events

Compliance Certifications (In Progress)
- SOC 2 Type II: Q3 2026 (audit underway)
- GDPR: Compliant (EU data residency options)
- ISO 27001: Planned Q4 2026
- HIPAA: Available via BAA for Confidential Compute customers
- PCI-DSS: Stripe-handled payment processing (Level 1 certified)

How Confidential Compute Works

Traditional cloud GPU providers (including decentralized ones) have a vulnerability: the GPU provider can theoretically access your data in GPU memory. io.net's Confidential Compute solves this:

Without Confidential Compute:

Your data → Unencrypted in GPU memory → Provider can read it ❌

With Confidential Compute:

Your data → Encrypted in TEE → Only your code can decrypt → Provider sees only encrypted data ✅

Technical Implementation:

Attestation: Before launching, io.net verifies the GPU node runs genuine TEE hardware (AMD SEV-SNP or Intel TDX)
Encrypted Launch: Your Docker container and data are encrypted with a key only your workload possesses
Memory Isolation: GPU memory is encrypted at the hardware level - provider's root access cannot read it
Secure Output: Results are encrypted before leaving the TEE, only you can decrypt

Example: Training a Proprietary Model

# Standard GPU (provider can access data)
io launch --gpu H100 --image your/training:latest
# Cost: $2.20/hr
# Security: Provider could theoretically snapshot GPU memory

# Confidential Compute GPU (encrypted)
io launch --gpu H100 --confidential-compute --image your/training:latest
# Cost: $2.40/hr (+$0.20/hr)
# Security: Provider sees only encrypted data, cannot access model weights or training data

Performance Impact:
Confidential Compute adds 2-5% overhead (slightly slower training/inference). For most workloads, this is negligible compared to the security gain.

Attestation Report:

# Verify your GPU is running in a genuine TEE
io attestation verify --instance io-h100-5f3a

# Output:
✅ TEE Platform: AMD SEV-SNP
✅ Firmware Version: 1.51
✅ Measurement: 3f7a...8c2d (matches expected)
✅ Provider cannot access guest memory

Decentralized Security Model: How It Works

The Challenge:
io.net aggregates GPUs from independent providers. How do you trust third-party hardware?

The Solution: Defense in Depth

Layer 1: Provider Vetting
- KYC verification: All GPU providers must verify identity
- Security audit: Automated scans for malware, rootkits, compromised drivers
- Hardware attestation: NVIDIA driver signatures verified, GPU firmware checked
- Network security: Providers must meet firewall, patching, and hardening requirements
- Insurance: Providers carry cybersecurity insurance ($1M+ coverage)

Layer 2: Runtime Isolation
- Container isolation: Docker/Kubernetes namespace isolation
- No provider access: Providers cannot SSH into your containers
- Separate networks: Your containers isolated from provider's network
- Ephemeral instances: Containers destroyed on stop, no data persistence on provider hardware

Layer 3: Encryption
- Data in transit: TLS 1.3 for all network traffic
- Data at rest: AES-256 for persistent volumes
- Data in use: Confidential Compute (TEE) for GPU memory

Layer 4: Monitoring
- Real-time security scans: Malware detection on provider nodes
- Anomaly detection: ML-based detection of suspicious provider behavior
- Reputation scoring: Providers with security incidents lose reputation, are deprioritized

Layer 5: Zero-Trust Architecture
- Assume compromise: Even if provider is malicious, they cannot access your encrypted data
- Verify everything: Continuous attestation that GPUs run in TEEs
- Least privilege: Providers have zero access to customer workloads

Comparison to Centralized Clouds:

Security Concern	AWS/Azure/GCP	io.net (Standard)	io.net (Confidential Compute)
Cloud provider can access data	✅ Yes (with insider threat)	✅ Yes (provider access risk)	❌ No (hardware-encrypted)
Data encrypted at rest	✅ Yes	✅ Yes	✅ Yes
Data encrypted in transit	✅ Yes	✅ Yes	✅ Yes
Data encrypted in use (GPU memory)	⚠️ Nitro Enclaves only	❌ No (standard GPUs)	✅ Yes (TEE)
Certifications	SOC 2, ISO 27001, HIPAA	SOC 2 in progress	SOC 2 in progress
Provider vetting	N/A (first-party)	✅ Yes	✅ Yes

For most enterprise workloads: Standard io.net security (without Confidential Compute) is comparable to AWS/Azure. Enable Confidential Compute for regulated industries or highly sensitive data.

Security Best Practices

1. Enable Confidential Compute for Sensitive Workloads

# Healthcare/financial data
io launch --gpu H100 --confidential-compute --disk-encryption byok

2. Use Private Networking

# No public IPs, SSH tunnel only
io launch --gpu A100 --private-network --ssh-tunnel

3. Implement Network Whitelisting

# Only allow access from your office IP
io firewall add --instance io-h100-7a3f --allow 203.0.113.10/32

4. Rotate API Keys Regularly

# Generate new API key, revoke old one
io api-key rotate --revoke-old

5. Enable Audit Logging

# Export all API calls to your SIEM
io audit-log export --destination s3://your-bucket/io-logs/

6. Use BYOK (Bring Your Own Key)

# Encrypt volumes with your KMS key
io launch --gpu H100 --encryption-key arn:aws:kms:us-west-2:123456789:key/abc-123

7. Implement Least Privilege RBAC

Roles:
- Admin: Full control (1-2 people)
- Developer: Launch GPUs, view logs (engineering team)
- Finance: View billing only (finance team)
- Read-only: View instances, no control (management)

8. Data Residency Controls

# Force GPUs in EU for GDPR compliance
io launch --gpu A100 --region eu-west --data-residency eu

Incident Response and Provider Monitoring

Real-Time Security Monitoring:
io.net's security team monitors providers 24/7:

Malware scans: Every 6 hours on all provider nodes
Vulnerability patching: Critical CVEs patched within 24 hours
Driver integrity: NVIDIA driver signatures verified on every GPU provision
Network anomalies: Unusual outbound traffic flagged and investigated
Reputation system: Providers with security incidents deprioritized or removed

Incident Response:
If a provider is compromised:
1. Automated isolation: Provider node immediately removed from marketplace
2. Customer notification: Affected customers notified within 1 hour
3. Workload migration: Active jobs auto-migrated to secure nodes
4. Forensic analysis: Provider investigated, banned if compromise confirmed
5. Post-mortem: Public incident report published (anonymized)

Example Incident (November 2025):
- What happened: Provider node in Asia detected running cryptominer alongside customer workloads
- Detection time: 12 minutes (anomalous GPU utilization pattern)
- Response: Node auto-removed from marketplace, 3 affected customer workloads migrated to new nodes
- Customer impact: 2-minute interruption, credits refunded
- Provider outcome: Permanently banned, security deposit forfeited

Data Residency and Compliance

GDPR Compliance (EU Customers):
- EU-only GPUs: Force GPU allocation in EU-West or EU-Central regions
- Data Processing Agreement (DPA): Available on request
- Right to deletion: Delete all data with cryptographic erasure
- Data export: Export all data in machine-readable format

# GDPR-compliant deployment
io launch --gpu A100 --region eu-west --data-residency eu --encryption-key your-kms

HIPAA Compliance (Healthcare Data):
- BAA available: Business Associate Agreement for covered entities
- Confidential Compute required: Mandatory for PHI (Protected Health Information)
- Audit logging: 7-year retention for HIPAA compliance
- Access controls: Enforce 2FA, SSO, and role-based access

PCI-DSS (Payment Data):
- Segment cardholder data: Use dedicated GPU clusters with network isolation
- Encryption: AES-256 at rest, TLS 1.3 in transit, TEE in use
- Quarterly scans: Vulnerability scans every 90 days
- Access logging: Track all access to cardholder data environments

SOC 2 Type II (In Progress):
- Audit timeline: Started February 2026, expected completion August 2026
- Scope: Security, availability, confidentiality controls
- Report availability: Public summary report, full report under NDA

Enterprise Support and SLAs

Standard Support (All Users):
- Email support: <24hr response time
- Discord community: Real-time help from io.net team and community
- Documentation: Comprehensive security guides, best practices

Enterprise Support ($5,000+/month):
- Dedicated Slack channel: Direct access to io.net engineering
- <2hr response SLA: Critical issues (security, outages)
- <8hr response SLA: High priority (performance, billing)
- Security consultation: Quarterly security reviews
- Custom SLAs: Available for $50,000+/year contracts

Security Incident SLA:
- Critical vulnerability: Patch within 24 hours
- Provider compromise: Affected customers notified within 1 hour
- Workload interruption: Auto-migration to healthy nodes within 5 minutes

Real-World Enterprise Deployments

Case Study 1: Healthcare AI Startup
- Use case: Training radiology AI models on patient X-rays (PHI)
- Requirements: HIPAA compliance, data cannot leave US
- Solution: US-only GPUs with Confidential Compute + BAA
- Result: Successfully trained models on 500K patient images, HIPAA audit passed
- Cost: 68% cheaper than AWS with same security controls

Case Study 2: Financial Services Firm
- Use case: LLM fine-tuning on proprietary trading data
- Requirements: Data cannot be accessed by third parties
- Solution: Confidential Compute + BYOK encryption + private networking
- Result: Fine-tuned Llama 3 70B on proprietary data, no data exposure
- Cost: $12,000 for 3-week training run vs. $38,000 on AWS

Case Study 3: Government Contractor
- Use case: NLP on classified documents (CUI - Controlled Unclassified Information)
- Requirements: FedRAMP equivalent security
- Solution: Custom security controls, US-only GPUs, dedicated provider pool
- Result: Processed 2M documents, passed security audit
- Status: io.net working on FedRAMP authorization (2027 target)

Can GPU providers access my data or models?

On standard GPUs, providers have root access to the physical hardware and could theoretically access data in GPU memory, though this violates Terms of Service and results in permanent ban. With Confidential Compute enabled ($0.20/hr premium), hardware-level encryption ensures providers cannot access your data even with physical access. For maximum security on sensitive workloads, always enable Confidential Compute.

Is io.net more or less secure than AWS/Azure/GCP?

io.net with Confidential Compute provides equivalent security to AWS Nitro Enclaves or Azure Confidential Computing - all use hardware-based Trusted Execution Environments. Standard io.net (without Confidential Compute) has slightly different risk profile: AWS relies on trust in Amazon; io.net relies on trust in independent providers plus technical controls (vetting, monitoring, encryption). Most enterprise teams consider them comparable, with Confidential Compute being the equalizer.

What happens if a GPU provider gets hacked?

io.net's zero-trust architecture assumes providers may be compromised. If a provider is hacked: (1) Confidential Compute prevents attackers from accessing encrypted GPU memory, (2) Network isolation prevents lateral movement to other customers, (3) Automated security monitoring detects anomalies and isolates the node, (4) Your workload auto-migrates to a healthy node within 5 minutes. You're credited for any downtime.

Can I use io.net for PCI-DSS or HIPAA workloads?

Yes, with appropriate configurations. For HIPAA: enable Confidential Compute, sign a Business Associate Agreement (BAA), use US-only GPUs, and implement audit logging. For PCI-DSS: segment cardholder data environments with private networking, use Confidential Compute, enable quarterly vulnerability scanning, and implement access controls. Contact [email protected] for compliance guidance specific to your use case.

Does io.net have penetration testing or bug bounty programs?

Yes. io.net conducts quarterly penetration tests by third-party security firms (reports available under NDA for enterprise customers). A public bug bounty program launched in March 2026 on HackerOne with bounties up to $50,000 for critical vulnerabilities. Submit security vulnerabilities to [email protected] or via HackerOne.

Get Started with Enterprise-Grade Security

Deploy secure GPU workloads on io.net:
- Confidential Compute - Hardware-encrypted GPU memory (+$0.20/hr)
- SOC 2 Type II - Certification in progress (Q3 2026)
- HIPAA/PCI-DSS - Compliant configurations available
- Private networking - Isolated VPCs, encrypted traffic
- Enterprise support - Dedicated security consultation

Contact enterprise security team → or view security documentation →

Last updated: April 2026 | Security features and certifications subject to change. Contact [email protected] for latest compliance status.