AUTHREX-ASSURE
The Signed Gate Between Test and Production
Today the decision to flip an autonomous system from testing to production is an email sign-off or a checkbox. ASSURE replaces it with a machine-checkable gate: seven configured assurance checks evaluated and recorded in sequence, then a cryptographically signed assurance record, a release recommendation rather than an Authorization to Operate, committed to a tamper-evident ledger.
A Release Recommendation, as a Pipeline Output.
- Release decision lives in an email or a pipeline checkbox
- No standardized, machine-checkable pre-production conditions
- Unverifiable after the fact: "we think it was tested"
- The gate that protected the test environment does not travel with the system
- Seven-stage pipeline run in assurance mode, one property per gate
- SATA provenance · ADARA robustness · IFF identity · HMAA authority bound · MAIVA integrity · FLAME deliberation · CARA rollback
- Pass → signed assurance record (a release recommendation) on the ledger
- Fail → the system stays in test, with the failing condition on record
One Artifact. Three Audiences.
Program Managers
A program office fielding an autonomous capability gets a single, auditable artifact, the signed assurance record, which is intended to provide attributable evidence that the configured assurance checks were completed and recorded; its evidentiary value depends on the completeness of the checks, the integrity of the test environment, key protection, and independent evaluation. That replaces "we think it was tested" with a signed, tamper-evident record of what was actually checked, whose reliability depends on key protection, ledger implementation, retention controls, and the integrity of the test process.
System Operators
Operators inherit a system that is intended to be prevented from exceeding its configured tier at the proposed software enforcement point demonstrated in synthetic simulation, subject to platform integrity, downstream-path integrity, protected keys, and correct integration; in the proposed workflow, configured authority bounds would be evaluated and recorded before a release recommendation; carrying equivalent controls into a deployed integration would require complete implementation, platform integrity, downstream-path integrity, key protection, and independent evaluation. The record is illustrative and is not a certification, an Authorization to Operate, legal approval, safety approval, airworthiness determination, or government release decision.
Oversight & Audit
Auditors and inspectors get a tamper-evident trail: which conditions were checked, when, with what result, and who authorized the release. An after-incident review can reconstruct the recorded inputs, checks, outputs, and authorization events available in the evidence package.
A Gap the Government Named Itself.
The U.S. government is deploying autonomous AI faster than it is writing the rules to govern deployment. ASSURE answers primary-source demands directly:
It maps to stated federal priorities
The March 2026 White House cyber strategy (President Trump’s Cyber Strategy for America) and NDAA §1533 (Artificial Intelligence Model Assessment and Oversight) both address assurance of AI systems before and during deployment. AUTHREX-ASSURE is a proposed reference design the author maps to that pre-deployment assurance theme. No directly comparable publicly documented reference design was identified in the sources reviewed for the underlying study; proprietary, classified, unreleased, or poorly documented capabilities cannot be ruled out.
It is deadline-backed by law
NDAA §1533 (Artificial Intelligence Model Assessment and Oversight, P.L. 119-60, enacted December 18, 2025) directs a cross-functional team by June 2026 and a DoD-wide AI assessment framework due June 2027. ASSURE is structured as a candidate pattern for that framework: a repeatable, signed, pre-production assessment.
It is whole-of-government
The pre-deployment gate is domain-agnostic. The same assurance pattern applies to a defense autonomy program, a civil-agency AI system under OMB M-25-21, and a critical-infrastructure controller, so a common assurance-record pattern may be adaptable across multiple agency and infrastructure contexts, subject to program-specific requirements and qualified assessment.
It produces accountable evidence
Government accountability depends on records. ASSURE's signed assurance record and ledger turn "was this checked before release?" from a matter of memory into a matter of cryptographic record, intended to support later oversight and reconstruction.
The Heilmeier Catechism, Answered Plainly.
Build a standardized, machine-checkable gate that produces an internal release recommendation for consideration by the accountable program authority when an autonomous AI system moves from test toward production, and that records the decision as a signed, auditable assurance record. Plainly: a pre-deployment evidence record designed to be hard to skip, subject to the stated key-protection and process assumptions.
Today it is a human sign-off, an email approval, or a checklist. Assurance and release practices vary across programs. In the public sources reviewed for this project, no directly comparable uniform architecture was identified for recording configured safety and authority checks as a signed, tamper-evident release-recommendation record. Proprietary, classified, unreleased, or program-specific capabilities cannot be excluded.
Running the same seven-stage authority pipeline in assurance mode as a pre-production gate, and emitting a cryptographically signed assurance record, a release recommendation rather than an Authorization to Operate, committed to a tamper-evident ledger. The novelty is treating the release recommendation as a formal pipeline output, not a human checkbox.
Program offices, operators, and oversight bodies care. If it works, "was this system properly assured?" becomes a verifiable record instead of a hope, and systems that do not satisfy the configured checks are assigned a hold recommendation in the proposed workflow instead of an automatic path to the field.
The main risks are that the assurance conditions are incomplete (a gate that checks the wrong things), and that the single-author mapping has not yet been independently validated. Both are stated openly; the simulation below shows the gate logic so it can be inspected and challenged.
The governance logic is software and adds negligible marginal cost; the signing root is a commodity secure element (the BLADE-AGENT-HSM reference is approximately $199 in parts). The cost is integration effort, not hardware.
The reference architecture and simulation exist now (self-assessed TRL 3 to 4). Converting it from a single-author design into an independently validated framework, the real work, aligns with the NDAA §1533 June 2027 horizon.
Midterm: an independent reviewer applies the assurance gate to a system and reports agreement or disagreement with the verdict. Final: the gate runs against a real system in a documented testbed and correctly holds an unsafe configuration while clearing a safe one.
Run the Assurance Gate Yourself.
Pick a candidate autonomous system, run the seven-stage check, and watch each gate evaluate in turn. Illustrative simulation of the gate logic, not operational validation.
All scenarios are synthetic. No real autonomous system is evaluated.
Model-Checked, Not Just Described.
Every AUTHREX application shares one model-checked authority core: the HMAA authority state machine, specified in TLA+ and model-checked across the stated finite model. The checker also caught a real S5 view-change regression during development, evidence the method finds defects rather than rubber-stamping them.
The profiles share a model-checked authority-state specification. Results apply to the finite model, properties, and assumptions analyzed and do not validate a spacecraft, vehicle, controller, or operational integration.
What This Rests On, and What It Is Not.
President Trump’s Cyber Strategy for America (March 2026 White House cyber strategy; author-mapped, not an endorsement) · NDAA §1533, Artificial Intelligence Model Assessment and Oversight (P.L. 119-60: cross-functional team by June 2026, DoD-wide AI assessment framework due June 2027) · cross-walks to NIST AI RMF 1.0 and draft NIST IR 8596 Cyber AI Profile · hardware anchor: BLADE-AGENT-HSM →
Reference architecture, self-assessed at approximately TRL 3 to 4: specified and simulated, not fielded or operationally validated. The condition-to-gate mapping is one researcher’s analytical judgment, released openly for independent review. The signed assurance record is an illustrative artifact, not a legal, regulatory, or agency certification, and no agency adoption or endorsement is implied.