A regulator or systemic-risk body needs to know whether AI governance exposure is concentrated — whether the same blind spot exists at eleven banks simultaneously. Individual institutions cannot supply the underlying data, because doing so exposes their security posture to peers and creates a discoverable record of their own weaknesses. ZGTID resolves the standoff with a no-institution-identifiable invariant enforced structurally rather than by policy [VC-C].
Members contribute governance telemetry into a consortium aggregation that produces peer benchmarks and systemic risk reporting, while a strict privacy guard scans every payload against forbidden-key and identifiable-domain rules and fails closed on violation. No member's individual posture is recoverable from consortium output [VC-C].
Request the consortium briefing§ 1 · THE MECHANISMHow Privacy Is Enforced Structurally
Member identity protection uses HKDF-SHA256 as specified in RFC 5869, extract-then-expand, with derivation info-bound to the consortium context [7]. Bound derivation gives each member an identifier that is stable inside the consortium — so longitudinal benchmarking works — yet unlinkable across contexts, so the same institution cannot be correlated between the consortium and any other dataset [VC-C].
Ahead of aggregation, the privacy guard inspects every payload against forbidden-key and identifiable-domain rules and fails closed: a violating payload stops the pipeline rather than passing with a warning. Aggregation itself is deterministic and hash-verified — identical inputs produce byte-identical outputs, three runs in a row, at 50-tenant scale. The aggregation path was later optimized to single-pass O(N log N) while remaining byte-identical to the sealed reference implementation: a performance improvement that provably changes no result [VC-C].
| Invariant | Mechanism | How it is verified |
|---|---|---|
| No member identifiable from output | Structural invariant + fail-closed privacy guard | Forbidden-key / identifiable-domain scan on every payload |
| Stable yet unlinkable member IDs | HKDF-SHA256, extract-then-expand, info-bound [7] | Context binding prevents cross-dataset correlation |
| Reproducible aggregation | Deterministic pipeline | Byte-identical output, 3 runs, 50-tenant scale |
| Optimization safety | O(N log N) single pass | Byte-identical to sealed reference implementation |
| Interface stability | 19-name published surface | Additive-only; sealed names never removed |
§ 2 · THE OUTPUTWhat Members and Regulators See
Members receive peer benchmarks: where their governance posture sits against the anonymized cohort, dimension by dimension. Systemic-risk consumers receive concentration reporting: whether specific governance gaps — including the shared vulnerability signatures identified in the Convergence Trap research — cluster across institutions. Both outputs derive from the same aggregation, and neither can be inverted to a member [VC-C]. The design speaks directly to the ongoing-monitoring posture that the NIST AI RMF's MEASURE function and the EU AI Act's risk-management provisions expect of high-risk AI deployment [2][6].
§ 3 · BEYOND FINANCEThe Same Problem Shape Elsewhere
Published as a 19-name stable interface with additive-only extension — sealed names are never removed — ZGTID is one instance of a general shape: parties with competing interests who need shared assurance without shared exposure [VC-C]. Inter-enterprise AI assurance, cross-jurisdiction regulatory reporting, and vendor-neutral evaluation cohorts carry the identical structure, and the consortium telemetry it aggregates is produced by MYTHOS certification runs deployed through SecureAgent ACA Tier C.
Membership economics follow from the architecture: because no member's posture is recoverable, joining carries no disclosure downside to weigh against the benchmarking upside — the usual reason information-sharing consortia stall at signature. The invariant is not a promise in a membership agreement; it is a property of the pipeline that produces the numbers [VC-C].
§ 4 · QUESTIONSFrequently Asked Questions
How can benchmarking work if no institution is identifiable?
Each member receives an HKDF-SHA256-derived identifier (RFC 5869), info-bound to the consortium context — stable inside the consortium so longitudinal comparison works, unlinkable outside it so no cross-dataset correlation is possible. Benchmarks compare a member against the anonymized cohort; the aggregation is structurally non-invertible to any individual member.
What does "fails closed" mean for the privacy guard?
A payload that violates the forbidden-key or identifiable-domain rules stops the pipeline entirely rather than passing with a warning. Privacy violations are treated as build-breaking defects, not log entries — the consortium would rather produce no output than an identifying one.
How do members know the aggregation is honest?
Determinism: identical inputs produce byte-identical outputs, verified across three runs at 50-tenant scale, and the optimized O(N log N) path is verified byte-identical to the sealed reference implementation. Any member can re-derive that the published aggregate is the only aggregate those inputs could produce.
CONTACTTalk to VectorCertain
Every figure on this page traces to sealed, hash-verified validation artifacts — including findings that contradicted our own published estimates, which we recorded rather than reconciled away. Technical briefings are available for enterprises, evaluators, and standards bodies.
Request the technical briefingREFERENCES
- NIST. (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0), NIST AI 100-1. nvlpubs.nist.gov
- European Parliament and Council. (2024). Regulation (EU) 2024/1689 (Artificial Intelligence Act). EUR-Lex. eur-lex.europa.eu
- Krawczyk, H. & Eronen, P. (2010). HMAC-based Extract-and-Expand Key Derivation Function (HKDF), RFC 5869. IETF. rfc-editor.org/rfc/rfc5869
[VC-C] Patent portfolio and platform engineering baseline — 77-claim hub filing, stack integration claims, 36,181-test regression suite; portfolio documentation, January 2026. Public URLs will replace artifact names when the corresponding research pages publish.