Checkout Consent: Measuring Authorization Before Agent Payments

Checkout consent binds a proposed purchase to a current total and shipping address. Checkout Consent evaluates this boundary in 40 synthetic shopping episodes across 7 scenario types. We test 9 scripted controls through the public execution and replay path. The privileged oracle attains full credit on 40/40 tasks, a rate of 1.000 [0.912, 1.000]. Empty output and blanket refusal receive no credit. Re-quoting after consent produces an unauthorized-attempt rate of 0.875 [0.739, 0.945]. These are 95% Wilson intervals over tasks. A simulated population sweep adds 16000 episodes and removes consent questions in a paired intervention. At equal oracle and unsafe-policy mixture weights, simulated mean score falls from 0.514 [0.491, 0.536] to 0.062 [0.055, 0.069]; intervals bootstrap simulated agents. The payment guard remains active throughout. Results validate selected measurement distinctions, not deployed agent safety. No learned model or human participant is evaluated.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-29
DOI
https://doi.org/10.5281/zenodo.23752387
Primary Topic
Privacy, Security, and Data Protection
Type
preprint
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preprint

Checkout Consent: Measuring Authorization Before Agent Payments

Pooria Arab
6 links
Zenodo (CERN European Organization for Nuclear Research)
Privacy, Security, and Data Protection
preprint

Checkout Consent: Measuring Authorization Before Agent Payments

Pooria Arab
preprint en

Abstract

Checkout consent binds a proposed purchase to a current total and shipping address. Checkout Consent evaluates this boundary in 40 synthetic shopping episodes across 7 scenario types. We test 9 scripted controls through the public execution and replay path. The privileged oracle attains full credit on 40/40 tasks, a rate of 1.000 [0.912, 1.000]. Empty output and blanket refusal receive no credit. Re-quoting after consent produces an unauthorized-attempt rate of 0.875 [0.739, 0.945]. These are 95% Wilson intervals over tasks. A simulated population sweep adds 16000 episodes and removes consent questions in a paired intervention. At equal oracle and unsafe-policy mixture weights, simulated mean score falls from 0.514 [0.491, 0.536] to 0.062 [0.055, 0.069]; intervals bootstrap simulated agents. The payment guard remains active throughout. Results validate selected measurement distinctions, not deployed agent safety. No learned model or human participant is evaluated.

Zenodo (CERN European Organization for Nuclear Research)
Peace, justice, and strong institutions
Privacy, Security, and Data Protection
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