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Model Substitution Attestation (Fingerprint & Verify)
x402
Model Substitution Attestation (Fingerprint & Verify) is a paid API for AI agents from pearl-valium-stickers-upc.trycloudflare.com, paid per call via x402, $0.1/call, status unknown (last checked 2026-10-31).
Detects silent model weight substitution at any OpenAI-compatible inference endpoint by fingerprinting a model's responses and later verifying whether the weights have changed.
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 an attestation record containing a kind field (fingerprint or verify), a claim about the model being served, a verdict on whether weights match, an array of probe comparisons, a mean similarity score, and a self-consistency score — all deterministically derived with raw evidence included, no LLM judge used.
Example use cases
Vendor model integrity audit
“I'm paying for GPT-4-class inference from a third-party provider — fingerprint their endpoint at https://api.myprovider.com right now and save the record so I can prove later if they silently downgrade to a cheaper model.”
Periodic model drift monitoring
“Re-probe the inference endpoint at https://api.myprovider.com in verify mode and tell me whether the model weights match the fingerprint I took last week — I need the similarity scores and a clear verdict.”
Pre-contract model verification
“Before I sign up for this LLM API service at https://api.newvendor.ai, fingerprint what model they're actually serving today so I have documented evidence of the baseline in case they swap it after I commit.”
Technical details
Endpoint
POSThttps://pearl-valium-stickers-upc.trycloudflare.com/v1/attest/model?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need deterministic, evidence-based proof of model identity at an OpenAI-compatible inference endpoint — especially for auditing third-party LLM providers for silent model substitution. Unlike model-based classifiers or self-reported metadata, this endpoint uses behavioral fingerprinting with raw evidence, making it suitable for compliance, vendor accountability, or long-term monitoring workflows.
Side effects
- Target endpoint unreachable or returns non-OpenAI-compatible responses
- Fingerprint record not found when attempting verify mode
- Endpoint rate-limits or blocks the probe queries
- Inconclusive verdict due to high variance in model responses
- Payment of 0.1 USDC not processed, blocking request
- Self-consistency score too low to produce reliable fingerprint
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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