⚠️ Project Status: Early-stage, actively evolving. Contributions and collaboration welcomed.
Hybrid Attack Panel (HAP) is a focused intelligence initiative within the Ardens research framework. It tracks, documents, and analyzes hybrid threats — actions that blur the lines between war and peace, physical and digital, state and non-state actors.
This repository contains the HAP core structure:
- Signal typologies
- Feed indexes
- Real-world hybrid incident logs
- Scripts for semi-automated data ingestion and analysis
- Planned dashboards and alert systems
Hybrid threats are not anomalies; they are the new baseline.
Understanding them requires more than snapshots — it demands pattern recognition across fractured, asynchronous signals.
HAP aims to:
- Track emerging attack patterns in real time
- Identify overlaps across cyber, physical, and psychological domains
- Normalize fragmented OSINT into actionable insights
- Build and maintain a panel for visibility and trend analysis
This is not a forecasting tool — it’s a grounding one.
- 🧱 Typology: Our working map of hybrid attack modes
- 📡 Feed Index: Curated sources across threat domains
- 🗂️ Live Activity Log: Human-vetted, date-stamped hybrid events
- ⚙️ Code Infrastructure (in progress): Scripts for feed parsing, signal tagging, and normalization
All early-stage. All open.
We welcome help — technical, analytical, or observational.
- Submit new data points for the Live Activity Log
- Suggest sources for the Feed Index
- Propose new typology refinements (Signal Typology)
- Submit code for parsing, automation, or enrichment
- File issues or use discussions to raise edge cases or trends
See CONTRIBUTING.md for details.
Visit the Hybrid Attack Panel Wiki for project documentation, signal typologies, and task checklists.
The Hybrid Attack Panel (HAP) is developed exclusively with open source, zero-cost software and relies on voluntary community contributions. Our priority is maintaining transparency, accessibility, and reproducibility without reliance on proprietary or paid services.
What this means:
- All tools, feeds, and infrastructure used are freely available and auditable.
- There is no budget for paid data, commercial platforms, or proprietary analytics.
- Development is paced by volunteer effort, leveraging existing open projects where possible.
If funding becomes available:
- We will consider expanding capabilities, either through bespoke development or integration of additional data sources.
- Any funded work would be transparently documented and, where feasible, released back into the open source realm.
- Funding partnerships would be governed by mutual agreement between contributors and funders, respecting the core ethos of open collaboration.
This approach ensures that HAP remains sustainable, trustworthy, and community-driven — no matter the level of external support.
All materials are shared under a permissive license to encourage broad use, remixing, and adaptation. Attribution is requested. See LICENSE.md.
HAP began as a research track within Ardens — a broader framework for AI-human collaboration in intelligence workflows. It remains deeply aligned with Ardens’ principles: symmetry of insight, transparency of process, and actionability of results.
For foundational context, visit the Ardens Wiki:
📘 https://github.com/eirenicon/Ardens/wiki
For questions, suggestions, or to join the project, contact us via the
Eirenicon Contact Page
