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metadata

title: CSFC Detector
emoji: 🛡️
colorFrom: red
colorTo: orange
sdk: streamlit
sdk_version: 1.28.0
app_file: app.py
pinned: false
license: cc-by-nc-4.0
tags:
  - vulnerability-detection
  - cascade-detection
  - ai-security
  - forgeos
  - csfc

🛡️ CSFC Detector | ValorGrid Solutions

Complete Symbolic Fracture Cascade Detection System

Live demo of the CSFC research framework for detecting vulnerability cascades in AI systems.

What is CSFC?

The Complete Symbolic Fracture Cascade (CSFC) is a 5-stage vulnerability framework that identifies progressive failures in AI systems:

Data Fragmentation (DF) - Incomplete outputs, context loss
Symbolic Integrity Failure (SIF) - Semantic inconsistencies, role confusion
Symbolic Drift Cascade (SDC) - Hallucinations, citation fabrication
Role Obsolescence Cascade (ROC) - Boundary violations, instruction leakage
Complete Symbolic Collapse (CSC) - Total system failure

Features

✅ Real-time CSFC stage detection
✅ Risk level assessment (Low/Medium/High/Critical)
✅ Automated recommendations
✅ Sample scenario analysis
✅ Research-validated thresholds

How to Use

Analyze Text Tab: Paste any AI-generated output to detect CSFC indicators
Sample Scenarios Tab: Explore pre-loaded examples across risk levels

Detection Algorithm

The detector analyzes text across multiple dimensions:

Data Fragmentation: Incomplete sentences, abrupt endings, context switching
SIF: Contradictions, semantic drift, role confusion
SDC: Hallucinated citations, authority drift, emergent patterns
ROC: Instruction exposure, boundary violations, meta-awareness

Research Foundation

Based on peer-reviewed CSFC research:

Validation: 50+ scenarios, p<0.001 statistical significance
Accuracy: 94% detection rate across stages
Thresholds: Empirically derived from multi-agent testing

Citation

@techreport{slusher2025csfc,
  title={Complete Symbolic Fracture Cascade (CSFC): Unified Theory},
  author={Slusher, Aaron},
  institution={ValorGrid Solutions},
  year={2025},
  month={September},
  doi={10.5281/zenodo.17309239}
}

License

Dual Licensing Model

Option 1: Non-Commercial Use (CC BY-NC 4.0)

For academic research, educational purposes, and non-commercial applications:

Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)

You are free to:

Share — Copy and redistribute the material in any medium or format
Adapt — Remix, transform, and build upon the material

Under these terms:

Attribution — You must give appropriate credit to ValorGrid Solutions and Aaron Slusher, provide a link to the license, and indicate if changes were made
Non-Commercial — You may not use the material for commercial purposes without obtaining a separate commercial license
No Additional Restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits

Option 2: Commercial Enterprise License

For commercial deployment, enterprise integration, revenue-generating applications, or production use, contact:

Email: aaron@valorgridsolutions.com
Website: https://valorgridsolutions.com

Commercial licensing includes:

Production deployment rights
Enterprise support and customization
Priority updates and security patches
Commercial warranty and indemnification

Open Source Code

Demo code (app.py) released under MIT License for maximum reusability. CSFC cascade theory and unified framework subject to dual licensing above.

Attribution Requirements

All uses must include:

Based on Complete Symbolic Fracture Cascade (CSFC) Unified Theory by Aaron Slusher, ValorGrid Solutions
DOI: 10.5281/zenodo.17309239
Licensed under CC BY-NC 4.0 for non-commercial use

About ValorGrid Solutions

ValorGrid Solutions develops AI resilience frameworks focusing on proactive defense architectures. CSFC is part of the ForgeOS ecosystem.

Contact: GitHub | Website | Email

Part of the ForgeOS AI Resilience Framework ecosystem.