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ShadowLight Network is a modular, AI‑assisted research framework built for cybersecurity professionals to explore threats, systems, and assumptions through structured, non‑directive analysis across complex environments.

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ShadowLight-RECON/ShadowLight-Network

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New here? Start with docs/quick_start.md.

ShadowLight Network

ShadowLight Network is a documentation‑first analytical framework designed to formalize how complex systems, behaviors, and decisions are examined, categorized, and understood.

ShadowLight is not an application, tool, or product implementation.
It is the underlying framework that makes structured analytical systems possible.

ShadowLight is the wheel — refined, intentional, and foundational.


Current Release

Version: v1.1.0
Status: Active Development (Conceptual Framework Stable)

This release solidifies ShadowLight’s core philosophy, architecture, analytical modes, and documentation structure.


What ShadowLight Is

ShadowLight Network provides:

  • A structured analytical philosophy
  • Clearly defined modes of analysis
  • A consistent architectural mental model
  • Documentation that prioritizes clarity, rigor, and intent
  • A foundation for future systems, tools, or implementations

ShadowLight is designed to be understood first, then applied.


What ShadowLight Is Not

To maintain integrity and focus, ShadowLight is not:

  • A runnable software application
  • A generic AI framework
  • A collection of loosely connected ideas
  • An implementation‑specific system

ShadowLight intentionally separates conceptual design from execution.


Documentation Overview

All core documentation lives in the docs/ directory and defines the system in full.

Included Documents

  • Philosophy & Design Principles
    Foundational intent, values, and guiding constraints.

  • Architecture
    How ShadowLight is structurally organized at a conceptual level.

  • Modes & Analytical Behaviors
    Distinct analytical states and how reasoning changes between them.

  • Intended Use Cases
    Where ShadowLight applies — and why.

  • Limitations & Non‑Goals
    Explicit boundaries to prevent misuse or misinterpretation.

  • Roadmap
    Directional evolution of the framework.

  • Versioning
    How changes are tracked and classified.

Each document is designed to stand on its own while reinforcing the whole.


Design Philosophy

ShadowLight prioritizes:

  • Precision over breadth
  • Structure over improvisation
  • Intentional limitations over unchecked expansion
  • Long‑term coherence over short‑term convenience

Every constraint is deliberate.


Contributing

ShadowLight Network welcomes disciplined, thoughtful contributions that improve clarity, consistency, and conceptual rigor.

All contributions are reviewed under the project’s documented philosophy and constraints.

Please read CONTRIBUTING.md before opening issues or pull requests.


Changelog

A complete record of notable changes is maintained in CHANGELOG.md.


License

License information is provided in the LICENSE file.


Final Note

ShadowLight Network is designed to be foundational.

It is meant to outlast individual tools, implementations, and trends — providing a stable analytical core others can build upon without redefining.

If you are using ShadowLight, you are standing on its framework — and that is intentional.

Responsible Use Notice

ShadowLight Network is provided for educational, research, and conceptual purposes only. Users are solely responsible for how the framework is applied.
See DISCLAIMER.md and SECURITY.md for details.

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ShadowLight Network is a modular, AI‑assisted research framework built for cybersecurity professionals to explore threats, systems, and assumptions through structured, non‑directive analysis across complex environments.

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