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AEGIS PROTECT

Sovereign endpoint security and system-integrity command center for the Omega Universe operator stack.

VERITAS Omega Status License Platform


Ecosystem Canon

Aegis Protect is the security and integrity layer of the VERITAS Omega sovereign operator stack. It operates entirely local — no cloud telemetry, no external model calls, no off-device data transmission — enforcing the Omega principle that sovereign infrastructure does not report to outside authorities. Aegis consumes threat intelligence from the host OS, cross-correlates it with static code analysis, and routes AI-assisted synthesis through a locally managed Ollama instance. Within the broader Omega Universe, Aegis functions as the trust-enforcement boundary: other nodes such as omega-brain-mcp and veritas-vault depend on the posture assertions Aegis produces. It is a tool for operators, not end users, and its output is audit-grade by design.


Overview

What it is

Aegis Protect Hardware Health & System Overview
Aegis Protect unified hardware health and system overview cockpit displaying real-time telemetry wrapped in the VERITAS gold-and-obsidian UI.

Aegis Protect is a self-contained Electron + Flask desktop application that provides:

  • Static code vulnerability scanning (regex and AST-based, offline)
  • Live system threat hunting against 40+ deterministic signatures across 11 execution categories
  • Process-to-network correlation for multi-vector threat narrative construction
  • Real-time hardware telemetry (CPU, GPU, memory, disk, battery, thermals)
  • Companion daemon lifecycle management (Ollama, VPN, hardware monitors)
  • Atomic file remediation with multi-level backup chaining
  • One-click PDF audit dossier generation (Veritas Compliance Report)

What it is not

Aegis is not an antivirus, not a network firewall, not a cloud SIEM, and not a managed detection and response (MDR) service. It does not replace endpoint protection platforms. It is an operator-grade local intelligence and remediation workbench.


Capabilities

The following capabilities reflect what is implemented in the current codebase.

Threat Hunting

Aegis Protect Security Threat Surface
Dynamic live threat hunting module identifying anomalous process structures and unusual network behavior payloads.
Capability Detail
Rule engine 40+ signatures across 11 categories: Persistence, Privilege Escalation, Payload Delivery, Lateral Movement, Evasion, Credential Access, Discovery, Collection, C2, Impact, Execution
Live correlation Cross-links anomalous processes with open network connections and scan findings
Process telemetry Real-time psutil-based process enumeration with parent/child chain inspection
LOLBin detection Pattern matching against known living-off-the-land binary abuse signatures

Code Scanner

Capability Detail
Secret detection Hardcoded API keys, tokens, passwords via regex patterns
Dangerous functions OS command injection vectors, unsafe deserialization, network binding exposure
Dependency hygiene Unpinned dependency detection across Python and JavaScript manifests
Remediation Closed-loop suggest-verify-resolve workflow with atomic _safe_write_file() and .aegis.bak / .bak.1 backup chains
Scan history Persisted scan records in aegis_scan_history.db for regression tracking

AI Analysis

Capability Detail
Model qwen2.5:7b via local Ollama instance (http://127.0.0.1:11434)
Isolation Zero external network calls; inference is fully air-gapped
Prompt hardening Input sanitization and length-guards to resist prompt injection from malicious file contents or manipulated telemetry
BSOD Watchdog Background thread monitors specific kernel driver conflicts (e.g., VirtualBox NDIS filter)

Hardware Telemetry

Capability Detail
Metrics CPU, GPU, memory, disk, battery, thermal pressure
Tuning Power and cooling profile management via ThrottleStop, MSI Center, Afterburner (MSI GE78HX native)
Dashboard Tab-aware polling UI to minimize resource consumption during background scanning

Reporting

Capability Detail
Format PDF audit dossier via veritas_pdf.py
Content Scanned assets, found vulnerabilities, threat correlations, system compliance status
Branding Veritas Compliance Report, operator-stamped

Architecture

┌─────────────────────────────────────────────────────────────┐
│                     AEGIS PROTECT                           │
│                   Electron Shell (Node)                     │
│                                                             │
│  ┌──────────────────────────────────────────────────────┐  │
│  │  Renderer Process  (src/renderer/)                   │  │
│  │  renderer.js · renderer_tasks.js                     │  │
│  │  renderer_system_status.js · renderer_weather_widget │  │
│  │  renderer_task_board.js · renderer_project_launcher  │  │
│  │  Tab-aware polling · IPC bridge via preload.js        │  │
│  └─────────────────────┬────────────────────────────────┘  │
│                         │ IPC (contextBridge)               │
│  ┌──────────────────────▼────────────────────────────────┐  │
│  │  Main Process  (src/main.js)                          │  │
│  │  Electron BrowserWindow · child_process spawn         │  │
│  │  Launches backend/app.py via Python                   │  │
│  └─────────────────────┬────────────────────────────────┘  │
│                         │ HTTP REST (localhost:5000)        │
└─────────────────────────┼───────────────────────────────────┘
                           │
┌─────────────────────────▼───────────────────────────────────┐
│                  Flask Backend  (backend/app.py)            │
│               Waitress · 128 threads · 127.0.0.1:5000       │
│                                                             │
│  /api/system      system_api.py    (OS metrics)             │
│  /api/security    security_api.py  (security checks)        │
│  /api/threats     threat_api.py    (threat hunt engine)     │
│  /api/ai          ai_engine.py     (Ollama AI synthesis)    │
│  /api/defense     defense_api.py   (active defense ops)     │
│  /api/scanner     scanner_api.py   (code vulnerability scan)│
│  /api/hardware    hardware_api.py  (telemetry)              │
│  /api/performance perf_api.py      (CPU/GPU/mem)            │
│  /api/tuning      tuning_api.py    (power/cooling profiles) │
│  /api/vpn         vpn_api.py       (VPN lifecycle)          │
│  /api/weather     weather_api.py   (local weather proxy)    │
│  /api/projects    projects_api.py  (project management)     │
│  report_api.py                     (PDF report generation)  │
│  correlation_api.py                (cross-signal correlation)│
│  lifecycle_api.py                  (companion daemon mgmt)  │
│                                                             │
│  ┌──────────────┐  ┌──────────────────┐                    │
│  │  aegis.db    │  │ aegis_scan_      │                    │
│  │  (telemetry) │  │ history.db       │                    │
│  └──────────────┘  └──────────────────┘                    │
└─────────────────────────────────────────────────────────────┘
                           │
              ┌────────────▼───────────┐
              │  Companion Daemons     │
              │  Ollama  (localhost    │
              │  :11434) — on-demand  │
              │  ThrottleStop          │
              │  MSI Afterburner       │
              └────────────────────────┘

Quickstart

Prerequisites

Requirement Notes
Windows 10/11 (64-bit) Primary supported platform
Node.js >= 18 For Electron shell
Python >= 3.11 For Flask backend
Ollama Required for AI synthesis; install from ollama.com

Pull the required Ollama model before first run:

ollama pull qwen2.5:7b

Development

REM 1. Install Node dependencies
npm install

REM 2. Install Python dependencies (backend)
pip install -r backend/requirements.txt

REM 3. Launch Electron + auto-spawned Flask backend
npm start

npm start invokes electron . which uses src/main.js as the entry point. The main process spawns backend/app.py automatically as a child process.

Build / Package

REM Portable Windows executable (AegisProtect.exe)
npm run build

REM Full Windows installer
npm run dist

Build artifacts are emitted to the dist/ directory. The asar bundle is disabled so backend Python files remain accessible at runtime.


Configuration

Environment Variables

Variable Default Purpose
OLLAMA_HOST http://127.0.0.1:11434 Override Ollama API base URL
AEGIS_BACKEND_PORT 5000 Flask listen port (change in backend/app.py if needed)

Key Config Paths (Windows)

Path Purpose
backend/aegis.db Primary SQLite database (telemetry, tasks)
backend/aegis_scan_history.db Scan result history
backend/schema.sql Database schema; applied by init_db.py
src/assets/icon.ico Application icon used for Windows packaging

Companion Tool Paths

The lifecycle manager (backend/lifecycle_manager.py) expects managed companions to be resolvable on PATH or at default install locations:

  • ollama — standard Ollama install
  • ThrottleStop — MSI GE78HX tuning (optional; only needed for power profile management)
  • MSI Afterburner — GPU tuning (optional)

Security and Privacy Posture

Data residency: All scan data, telemetry, threat findings, and AI-generated analyses remain on-device. No data leaves the host.

AI isolation: The ai_engine.py blueprint routes all inference to the local Ollama endpoint (127.0.0.1:11434). No external model API calls are made.

Prompt hardening: User-controllable inputs (file paths, file contents, process names) that reach the AI prompt layer are sanitized and length-bounded before injection. This reduces the blast radius of adversarially crafted files designed to manipulate the AI output.

Atomic writes: All file remediation operations use _safe_write_file(), which writes to a staging path and renames atomically. Backup chains (.aegis.bak, .bak.1) are maintained before any overwrite.

Local binding only: The Flask backend binds exclusively to 127.0.0.1:5000. It is not reachable from external network interfaces.

What is not guaranteed: Aegis does not provide kernel-level tamper protection, signed binary verification, or hardware root-of-trust attestation. It is not a replacement for a full endpoint detection and response (EDR) solution.


Threat Model

Trust Boundaries

[ Operator (local user) ]
        |
        v
[ Electron Shell — IPC/contextBridge ]  <-- trust boundary 1
        |
        v
[ Flask Backend — localhost:5000 ]      <-- trust boundary 2
        |
        +---> [ SQLite databases ]
        |
        +---> [ Ollama — localhost:11434 ]
        |
        +---> [ Host OS APIs (psutil, subprocess) ]

In Scope

  • Malicious file contents: Files scanned by the code scanner may contain adversarially crafted strings designed to manipulate regex results or inject into AI prompts. Aegis applies sanitization to mitigate this.
  • Compromised Ollama model outputs: AI-generated text is treated as untrusted and rendered as plain text; it is never executed.
  • Path traversal in scanner: The scanner enforces bounds checks to prevent scanning outside the designated project directories.
  • Multi-threaded data races in the backend: Covered by destruction campaign tests (Wave 1 & 2).

Out of Scope

  • Physical access attacks: Aegis does not protect against an attacker with physical access to the machine.
  • Kernel/hypervisor compromises: Below the OS abstraction layer Aegis operates on.
  • Supply chain attacks on Ollama or Python packages: Operator is responsible for verifying dependency integrity.
  • Network-level attacks from external hosts: The backend is localhost-only; external network attack surface is zero by design.
  • Other users on the same host: Aegis is a single-operator tool; multi-user isolation is not implemented.

Roadmap

Item Status
Static code scanner + closed-loop remediation Implemented
Live threat hunt engine (40+ signatures) Implemented
Process-network correlation engine Implemented
AI synthesis via local Ollama Implemented
Hardware telemetry dashboard Implemented
Companion daemon lifecycle manager Implemented
PDF audit report generation Implemented
BSOD watchdog Implemented
Cross-platform support (macOS / Linux) Planned
Veritas Vault integration for encrypted finding storage Planned
omega-brain-mcp protocol bridge for distributed threat correlation Planned
Headless / server-mode operation Planned
Formal threat intelligence feed ingestion (STIX/TAXII) Planned

Omega Universe Cross-Links

Aegis Protect is one node in the VERITAS Omega sovereign operator ecosystem. Related repositories:

Repository Role
omega-brain-mcp Central MCP reasoning hub; planned consumer of Aegis posture data
veritas-vault Encrypted sovereign secret and credential store
Ollama-Omega MCP bridge that exposes local Ollama models to any IDE
drift Drift detection and configuration change tracking
SovereignMedia Sovereign local media and content management
sovereign-arcade Front-facing operator showcase for the Omega stack

🌐 VERITAS Omega Ecosystem

This project is part of the VERITAS Omega Universe — a sovereign AI infrastructure stack.

License

MIT License. See LICENSE for full terms.

Copyright (c) 2026 RJ Lopez / VrtxOmega

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Hardware governance and system security platform — stress-tested to 73,762 adversarial events at 0% error rate. Electron + Python with VERITAS pipeline integration.

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