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Model Attestation & Substitution Detection
x402
Model Attestation & Substitution Detection is a paid API for AI agents from dev-5090-box.tailfb4c1f.ts.net, paid per call via x402, $0.1/call, status unknown (last checked 2026-10-12).
Fingerprints or verifies an OpenAI-compatible inference endpoint to detect silent model substitution by the seller
Price / call$0.1
Success—
StatusUnknown
How this service works
Proof-of-Model: detect silent model substitution at any OpenAI-compatible inference endpoint. mode=fingerprint records what a seller serves today; mode=verify re-probes later and proves whether the weights changed. Deterministic, evidence included, no model used to judge.
Output
Returns a structured attestation result including a kind field indicating the probe type, a claim about the model identity, a verdict on whether the model matches the fingerprint, an array of per-sample comparison results, a mean_similarity score, and a self_consistency_now score reflecting current output stability.
Example use cases
Baseline model fingerprint before purchase
“I'm about to start paying for inference from a vendor claiming they run Qwen3-72B — fingerprint their endpoint now in mode=fingerprint so I have a cryptographic record of what they're actually serving today.”
Verify model hasn't been swapped mid-contract
“It's been two weeks since I fingerprinted that vendor's endpoint — re-probe it in mode=verify and tell me whether the mean_similarity score confirms they're still serving the same model or if there's been a substitution.”
Audit third-party AI reseller integrity
“I'm reselling inference from a third-party provider and my customers are complaining the outputs feel different — run an attestation check and give me the verdict and self_consistency_now score so I can prove whether the underlying model changed.”
Technical details
Endpoint
POSThttps://dev-5090-box.tailfb4c1f.ts.net/v1/attest/model?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need cryptographic or statistical proof that an inference provider is actually serving the model they claim — especially before signing contracts, after suspicious output quality changes, or as a recurring integrity check in automated AI procurement pipelines. Prefer this over manual output inspection when you need a quantified similarity verdict and documented evidence of substitution.
Side effects
- Endpoint unreachable or returns non-200 — attestation cannot complete
- Model serves stochastic outputs causing low similarity scores even without substitution
- Seller applies output filtering that defeats fingerprinting probes
- mean_similarity near threshold makes verdict ambiguous
- Payment of 0.1 USDC not processed — request blocked by x402 paywall
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| kind | string | |
| claim | string | |
| verdict | string | |
| comparisons | array | |
| mean_similarity | number | |
| self_consistency_now | number |
Tags
x402
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