Update README.md
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README.md
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@@ -15,4 +15,333 @@ models:
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- llama3-8b-8192
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thumbnail: >-
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https://cdn-uploads.huggingface.co/production/uploads/67c714e90b99a2332e310979/L02-prFfHa7eBZGVf4uvR.jpeg
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| 15 |
- llama3-8b-8192
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thumbnail: >-
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https://cdn-uploads.huggingface.co/production/uploads/67c714e90b99a2332e310979/L02-prFfHa7eBZGVf4uvR.jpeg
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+
---
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+
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Purple Team Code Workbench
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<p align="center">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/67c714e90b99a2332e310979/L02-prFfHa7eBZGVf4uvR.jpeg" width="720" alt="Purple Team Code Workbench Banner"/>
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</p>
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<p align="center">
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<strong>Streamlit-powered code generation and workflow orchestration surface for authorized purple-team operations.</strong>
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</p>
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<p align="center">
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<img alt="Python" src="https://img.shields.io/badge/python-3.11%2B-blue">
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<img alt="Streamlit" src="https://img.shields.io/badge/streamlit-1.57.0-red">
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<img alt="License" src="https://img.shields.io/badge/license-Apache--2.0-green">
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<img alt="Security" src="https://img.shields.io/badge/focus-purple--team-purple">
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</p>
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⸻
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Overview
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Purple Team Code Workbench is a Streamlit-based operational interface designed for structured, scope-aware security engineering workflows.
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The platform focuses on:
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* Authorized assessment workflows
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* Defensive and adversarial simulation support
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* Code generation for security operations
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* Evidence handling and finding management
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* Prompt-assisted workflow acceleration
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* Report artifact generation
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* Research and analysis augmentation
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The system is intentionally structured around controlled workflows rather than unrestricted autonomous execution. Because the internet already contains enough entropy generators wearing hoodies and calling themselves “operators.”
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⸻
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Core Design Principles
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Scope-First Architecture
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Every workflow begins with explicit authorization and target definition.
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The system is designed to reduce:
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* accidental scope drift
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* unsafe automation
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* uncontrolled execution paths
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* ambiguous operational state
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⸻
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Human-in-the-Loop Control
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The workbench assists analysts and engineers rather than replacing operational judgment.
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Generation ≠ execution.
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All generated output should be reviewed before use.
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⸻
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Evidence-Centric Workflow
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Outputs are treated as operational artifacts:
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* findings
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* prompts
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* code snippets
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* reports
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* remediation notes
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* validation records
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The system emphasizes traceability and reproducibility over “magic AI behavior.”
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A tragically rare design choice in 2026.
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⸻
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Features
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Current Capabilities
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* Streamlit-based UI
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* Scope-gated workflow controls
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* Security code generation surface
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* Passive recon helpers
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* Structured findings management
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* Markdown report export
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* Multi-model workflow support
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* Hugging Face Space deployment compatibility
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⸻
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Planned Capabilities
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* Agent orchestration
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* Prompt chaining
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* Workflow templates
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* Typed finding schemas
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* Evidence graphing
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* Drift-aware execution state
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* Multi-provider inference routing
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* Report diff/version tracking
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* Local LLM runtime support
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* LangGraph integration
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* MCP-compatible tool surfaces
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⸻
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Supported Models
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Current configured models:
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Model Purpose
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HauhauCS/Gemma-4-E4B-Uncensored-HauhauCS-Aggressive Experimental coding and reasoning
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DeepHat/DeepHat-V1-7B Security-oriented generation workflows
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llama3-8b-8192 General-purpose assistant workflows
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Model availability depends on provider access and deployment configuration.
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⸻
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Repository Structure
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.
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├── app.py
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├── requirements.txt
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├── README.md
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├── assets/
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├── workflows/
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├── prompts/
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├── reports/
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├── utils/
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└── components/
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Recommended modularization:
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Directory Purpose
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workflows/ Workflow orchestration logic
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prompts/ Prompt templates and chains
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reports/ Generated report artifacts
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utils/ Shared utilities
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components/ Streamlit UI components
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assets/ Static images and branding
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⸻
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Installation
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Local Development
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Clone the repository:
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git clone https://github.com/your-org/purple-team-code-workbench.git
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cd purple-team-code-workbench
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Create a virtual environment:
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python -m venv .venv
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Activate the environment:
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Linux/macOS
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source .venv/bin/activate
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Windows
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.venv\Scripts\activate
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Install dependencies:
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pip install -r requirements.txt
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Run the application:
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streamlit run app.py
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⸻
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Hugging Face Spaces Deployment
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This repository is compatible with:
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* Hugging Face Streamlit Spaces
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* CPU deployments
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* OAuth-enabled Spaces
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* External inference providers
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Example metadata:
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sdk: streamlit
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sdk_version: 1.57.0
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app_file: app.py
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license: apache-2.0
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⸻
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Security Philosophy
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This project is intended for:
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* authorized testing
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* defensive research
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* purple-team simulation
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* workflow engineering
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* educational environments
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* internal security operations
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This repository is not intended for:
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* unauthorized access
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* destructive automation
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* malware deployment
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* credential theft
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* persistence tooling
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* uncontrolled exploitation
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Users are responsible for complying with all applicable laws and authorization requirements.
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Tiny administrative detail. Society gets strangely emotional about “cybercrime.”
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⸻
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Recommended Operational Controls
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If deploying in production environments:
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* Require authentication
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* Log workflow activity
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* Separate trusted/untrusted prompts
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* Sandbox execution environments
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* Restrict outbound networking
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* Validate generated artifacts
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* Maintain immutable audit trails
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* Enforce scoped execution policies
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⸻
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Example Workflow
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Scope Definition
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↓
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Passive Recon
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↓
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Evidence Collection
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↓
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Finding Classification
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↓
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Code/Prompt Generation
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↓
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Human Validation
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↓
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Report Export
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⸻
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Development Roadmap
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Phase 1
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* Scope-gated workflows
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* Findings management
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* Report export
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* Prompt surface
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Phase 2
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* Agent coordination
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* Structured memory
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* Typed contracts
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* Multi-model routing
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Phase 3
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* Drift-aware orchestration
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* Evidence graphs
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* Policy enforcement engine
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* Autonomous validation loops
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⸻
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Contributing
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Contributions should prioritize:
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* clarity
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* safety
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* reproducibility
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* deterministic behavior
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* typed interfaces
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* operational traceability
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Before submitting:
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* run linting
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* validate workflows
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* document assumptions
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* avoid opaque automation behavior
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⸻
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License
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Licensed under the Apache 2.0 License.
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See the LICENSE file for details.
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⸻
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Disclaimer
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This project is provided for authorized security research, defensive engineering, and educational purposes only.
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The maintainers assume no liability for misuse, unauthorized deployment, or operational damage caused by derivative implementations.
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Because eventually someone always tries to turn a workflow engine into a cyberpunk side quest.
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⸻
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Acknowledgements
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Built with:
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* Streamlit
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* Hugging Face
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* Python Software Foundation
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Inspired by structured operational engineering, purple-team methodology, and the stubborn belief that security tooling should behave like systems engineering rather than ritual magic.
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