Why does running my prompt inside an encrypted VM not actually keep it private?
Opportunity
Confidential computing via Intel TDX and AMD SEV-SNP is the leading approach for private AI inference: user memory is encrypted and the cloud operator is architecturally blocked from reading it. TDXRay, published at IEEE S&P 2026 by UC San Diego, CISPA, and Google, showed that a host can reconstruct user prompts word-for-word at over 90 percent similarity by monitoring tokenizer cache access patterns without ever decrypting guest memory. A separate October 2025 disclosure showed that a $1,000 DDR5 bus interposer can extract attestation keys from both TDX and SEV-SNP hardware outright, making attestation forgery practical with commodity equipment. The only known software mitigation, oblivious RAM, imposes latency overhead that makes production inference uneconomical. An IDC survey from December 2025 found 84 percent of organizations adopting confidential computing cite attestation validat
Why it matters
If the hardware primitive underpinning private AI inference leaks prompt content under a physical or microarchitectural attack, every higher-layer privacy guarantee built on top of it is void.
How I score the opportunity
The Opportunity Score is my own read, not a measurement: how much it hurts, how often it bites, and how little exists to solve it today. Higher means I think it is more worth building.
How much pain it causes when it shows up.
How often people actually run into it.
How little good tooling exists for it today.
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