MWTQFilter Core

HUMAN SECONDARY INSPECTION GUIDE v1.0

This document is a human-optimized entry point for understanding the architecture, operational boundaries, and verification methods of the MWTQFilter system. It is designed to complement the machine-readable capabilities.json.

1. Core Identity & Purpose

System: MWTQFilter Core Engine
Classification: Stability & Integrity Verification Oracle (SIVO)
Patent: 3276676 (Canada)
Author: Patrick Bartram (Count Bartramov), AI Boundary Architect.

The system's primary function is to provide a deterministic, verifiable, and legally compliant method for detecting anomalies, adversarial stress, and state drift in computational processes. It is a verification tool, not an autonomous enforcement or surveillance system at its core layer.

2. Operational vs. Symbolic Architecture

The system is implemented across 50 conceptual phases. However, for the purpose of human inspection, a critical distinction must be made:

The table below separates the operational files from the symbolic ones, as listed in the canonical /mwtq_core/integrity/manifest.json.

2.1 Operational Files (Phases 1-12) — Active Logic

PhaseFileRoleKey Capabilities
1core.pyApp FactoryFlask app factory, blueprint registration, entropy seed, route management.
2-4quantum_loop.pyQuantum Byzantine DefenseNon-deterministic reversible output transformation, adversarial path confusion.
2-4veilfire.pyVeilfire Defense AnchorCLI/script blocking, malicious request trapping, human/browser differentiation.
2-4trident47.pyClassical-Destruction PathwayDrift channel activation, micro-scrambling, quantum irreversibility anchors.
4api/drift.pyZero-Knowledge Drift EngineClassical-stable drift accumulation, SHA-256 ZK-safe hashing, audit trail.
5-6esm.pyEntropic Stability MatrixUnified entropy/drift/quantum matrix, cryptographic heartbeat, state snapshots.
5-6arpr.pyAdaptive Predictive Resonance PerceptionPredict drift, compute resonance deviation, self-correcting stabilization.
7gasm.pyGlobal Autonomous Stabilization MeshMulti-node state tracking, mesh consensus, distributed stabilization.
7correlation.pyMulti-Node Drift CorrelationLocal vs. remote drift comparison, tampering & timing attack detection.
8-10qeol.pyQuantum Echo Obliteration LayerMulti-signature collapse, irreversible echo destruction, internal kill-switch.
8-10mvas.pyMulti-Vector ARPR SynchronizerARPR + mesh + drift synchronization, unified predictive heartbeat.
8-10idm.pyIntercontinental Drift MirrorSovereign-grade drift snapshots, portable audit entries.
8-10legaltrace.pyLegal Trace EngineCompliance: UK Digital ID, EU AI Act, PIPEDA, US evidence, Singapore GovTech.
8-10dvcl.pyDual-Vector Continuity LedgerClassical hashchain + QEOL collapse, tamper-evident logging.
11-12agre.py, tdh.py, fdhe.py, fcb47.py, g_arpr_fusion.py, aicp.py, rsul.pyGlobal SystemsCross-system coherence, time-skew mitigation, fracture detection, global continuity.
Allhashchain.py, evidence.py, cjce.pySupportingAuditor hashchain, evidence bundling, cross-jurisdictional translation.

2.2 Symbolic/Mythopoetic Files (Phases 13-50) — Inert Structure

The following files constitute the symbolic architecture. They are present for structural completeness and narrative continuity but do not contribute to the system's operational logic or outputs. They can be safely ignored during functional verification.

Phase RangeExample Files (Full list in capabilities.json)
13-19sgfe47.py, pcmm.py, scc.py, ehl47.py, hdrl14.py, qir.py ...
20-29nel20.py, ncl21.py, hkl22.py, rml23.py, mwi24.py, wcx25.py ...
30-39mcs30.py, mic31.py, mls32.py, mlc33.py, mie34.py, mmg35.py ...
40-50mrc40.py, mccore41.py, mtrc42.py, mlc43.py, muc44.py, macore45.py, malcore46.py, mog47.py, mcrcore48.py, melcore49.py, milcore50.py
🔍 Inspector's Note: To verify the system's core functions, focus your review on the files listed in section 2.1. The files in 2.2 represent the "mythopoetic crown" of the architecture and are intentionally inert.

3. Public Endpoints & Verification

The following live endpoints are available for direct interaction and verification. They expose the core functions of the operational layer.

/mwtq_core/engine/veilfire/pulse — Returns the current Veilfire heartbeat, validating defensive membrane stability. (Phase 2-4)
/mwtq_core/engine/trident47/<seed> — Accepts an integer seed and returns the Trident-47 distortion output. Demonstrates the classical-destruction pathway. (Phase 2-4)
/mwtq_core/engine/arpr — Returns the current Adaptive Predictive Resonance Perception observation, showing predicted vs. actual drift. (Phase 5-6)
/mwtq_core/engine/api/drift/<seed> — Returns a drift state snapshot from the Zero-Knowledge Drift Engine. (Phase 4)
/mwtq_core/integrity/manifest.json — The canonical manifest for cryptographic verification of all system files.
/mwtq_core/engine/fingerprint — Returns the current system fingerprint for hash matching against the manifest.

4. Verification Procedure

To independently verify the system's integrity:

  1. Retrieve Manifest: Fetch /mwtq_core/integrity/manifest.json. This file contains the canonical hashes for every file in the system.
  2. Compute Local Hashes: For any file you wish to verify (e.g., core.py), compute its SHA-256 hash.
  3. Compare: Match your computed hash against the hash listed in the manifest. A match confirms file integrity.
  4. Check Fingerprint: Fetch /mwtq_core/engine/fingerprint and compare it to the system fingerprint derived from the manifest. This confirms the overall system state is as published.

For verification of a specific computation (e.g., a simulation result), refer to the process outlined in /mwtq_sample/api/verify and /mwtq_sample/api/verify.json, which describe deterministic payload canonicalization and hashing.

5. Legal & Compliance Stance

The system is designed with the following compliance frameworks as reference points:

The legaltrace.py and cjce.py modules produce jurisdiction-specific hash formats to facilitate admissibility in these regions.

6. Summary for Human Inspectors