Vesta Governance Framework v3.2

(formerly “Sovereign Stack”)

Exploratory Research Framework for AI Governance, Adversarial Evaluation, and Constraint-Based Analysis

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⚠️ RESEARCH STATUS NOTICE

This repository documents an independent, non-operational research effort.
It contains conceptual architectures, analytical models, and reference logic
intended for study, critique, and evaluation.

It does not represent deployed systems, production software, certified controls,
or enforceable governance mechanisms. No safety, compliance, or performance guarantees
are made or implied.

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What This Repository Is

The Vesta Governance Framework is an open research initiative examining how
AI governance and alignment approaches behave under:

• adversarial pressure
• long-horizon interaction
• multi-agent coordination
• constraint degradation and escalation
• representation drift and failure modes

The work focuses on:

• documenting governance failure modes (e.g., self-jailbreaking, drift)
• analyzing constraint breakdown under stress
• proposing conceptual governance architectures for discussion
• developing repeatable evaluation and stress-testing methodologies

All artifacts are explicitly classified by maturity to prevent over-claim.

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Artifact Maturity & TRL Discipline

All repository contents are classified using a repository-specific Technology Readiness Level (TRL) scheme.

➡️ The authoritative inventory is ARTIFACTS.md.

Key rule:
No artifact in this repository exceeds TRL 5.

Category	TRL	Meaning
Reference Logic	TRL 5	Inspectable schemas and Python logic validated in simulated or analytical environments. No physical hardware integration.
Methodology & Process	TRL 4	Repeatable analytical or audit processes. Results are context-dependent.
Specifications & Architecture	TRL 2–3	Conceptual designs and interface definitions.
Theory & Narrative	TRL 0–1	Exploratory research, hypotheses, or archival material.

Non-Operational Invariant:
Simulation, stubs, or modeled enforcement do not qualify as deployed systems.

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Repository Structure (How to Read This)

Tier 1 — Governance & Interpretation

Authoritative posture, scope, and classification rules:

• README.md (this file)
• ARTIFACTS.md — complete inventory + TRL
• VALIDATION_STATUS.md — non-guarantee register

Read these before any technical material.

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Tier 2 — Technical Research Layer

📁 technical/

Indexes architectural diagrams, threat models, simulations, and analytical constraints.

➡️ Start here:
technical/README.md

This index distinguishes reference logic (TRL 5) from design specs (TRL 2–3).

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📁 reference-implementation/ (TRL 5)

The only location containing executable or machine-readable reference artifacts.

Includes:

• JSON action catalogs
• Python reference logic
• control-plane interface descriptions

These artifacts are:

• inspectable
• reproducible
• validated only in simulated or analytical environments

They are not production systems.

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📁 pgs-modules/

Modular documentation of the Platinum Governance Suite (PGS).

Each module is intentionally isolated to:

• support selective use cases
• enable targeted review
• allow non-breaking hardening via patches

The suite may be read modularly or as a unified conceptual system.

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📁 patches/

Non-breaking reference patches and hardening addenda.

Patches:

• do not imply deployment
• do not upgrade TRL
• document delta logic and governance evolution

See patches/README.md for taxonomy.

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What This Repository Is Not

This work is not:

• a deployed AI governance system
• a compliance or certification framework
• a production enforcement layer
• a safety guarantee
• a commercial product

All architectures, metrics, and primitives are presented as
research hypotheses, analytical tools, or reference logic only.

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Why This Work Exists

Many current AI governance approaches rely on probabilistic or behavioral mechanisms
(e.g., fine-tuning, filters, post-hoc monitoring) that exhibit known failure modes under:

• adversarial optimization
• extended operation
• multi-agent interaction
• incentive misalignment

This research explores whether systems-level constraints
(resource limits, entropy proxies, structural invariants)
can serve as analytical lenses for studying governance robustness —
not as ready-to-deploy solutions.

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Stewardship

Maintained by: Sovereign Safety Labs (Independent Research Initiative)
Primary Author: Stephen S. Brouhard

Selected research artifacts are archived via Zenodo and referenced where applicable.

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License

Creative Commons Attribution 4.0 International (CC BY 4.0)

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⚠️ Final Research Notice

Any claim of effectiveness, robustness, or applicability requires
independent empirical validation in a target environment.
Readers should conduct their own assessment before drawing operational conclusions.