Separating Disclosure from Authorization: Field-Tier Minimization for Agent Action Mediation
cs.CR, cs.SE
Submitted: 2026-08-26
Updated: 2026-08-26
Comments: 19 pages, 2 figures, 5 tables. Describes an implemented system in private pilot deployment
Code: https://github.com/Aurite-ai/agent-verifier
License: http://creativecommons.org/licenses/by/4.0/
The gist: A system that authorizes an action must see enough of it to decide, and a system that attests to its decision must record enough to be audited.
Terminology
Abstract
A system that authorizes an action must see enough of it to decide, and a system that attests to its decision must record enough to be audited. Both pressures push raw action parameters -- recipients, payment memos, record identifiers -- into an append-only ledger that cannot delete them. We show the two are separable. We classify each parameter field, not each action class, into three tiers: fields a policy may legitimately match on, which cross raw; fields that are policy-relevant but identifying, which cross only as projections such as an email domain or a templated route shape; and fields with no legitimate policy use, which never leave the workload. The central property is that the ledger's commitment is a canonical digest of the full, unminimized parameters, computed before minimization runs. The commitment is therefore independent of the tier table: reclassifying a field changes what is disclosed without invalidating a historical entry, reopening a hash, or altering what an offline verifier checks. Tier table, policy schema and wire schema are generated from one per-action declaration, so the deciding and recording parties cannot hold different rules. We then address a question the architecture forces: which party should compute each attested fact? We argue it is settled by which party could lie about it undetectably, and derive three answers within one request -- the client computes the parameter digest, being the only party holding the data; it is structurally prevented from naming the definition that governed it, since that would write a false statement into a signed ledger; and it attests which tier table it applied, so divergence is detectable. We give a leakage analysis of each projection, report an incident in which a first-cut projection preserved the identifier it was written to remove, and state the residual trust the design does not eliminate.
Sources
- AgentRiskBOM: A Risk-Scoping Security Bill of Materials for Agentic AI Systems
- Cedar: A New Language for Expressive, Fast, Safe, and Analyzable Authorization (Extended Version)
- AI Identity: Standards, Gaps, and Research Directions for AI Agents
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