Confidential computing: what it means for data in use protection

TL;DR: Confidential computing has evolved from a niche processor feature into an ecosystem spanning CPUs, GPUs and every major cloud, according to Fortanix, while remaining limited by trust assumptions, attestation maturity and provider re-entry into the TCB. The governance shift is from assuming infrastructure to verifying it, and that changes how sensitive workloads should be designed.

Editorial analysis by NHI Mgmt Group, based on content published by Fortanix: “10 years of Confidential Computing at Fortanix”.

Key questions

Q: How should organisations decide which workloads need confidential computing first?

A: Start with workloads that process regulated data, partner data, or high-value secrets where exposure in memory would create material risk.

Q: Why does attestation matter more than encryption alone for data in use?

A: Encryption keeps memory or data unreadable, but it does not prove that the right code is running.

Q: What are the signs that a confidential computing deployment still trusts too much?

A: The main warning signs are mandatory provider-managed components, opaque firmware updates, attestation services you cannot inspect and secret release that happens before proof of execution.

Practitioner guidance

• Define trust boundaries by workload sensitivity Map which applications can tolerate operator visibility and which require confidential execution, then align those workloads to the smallest viable trust base.
• Require attestation before secret release Do not hand over keys, tokens or data until the platform proves the expected code, firmware and hardware state.
• Review provider-controlled components inside the boundary Document any paravisor, attestation service or firmware path the cloud provider can change and decide whether that trust is acceptable.

Bottom line: Confidential computing reduces trust in the infrastructure operator by proving runtime state before sensitive data or secrets are released.

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