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Vulnerability Oriented Red-teaming for AI Knowledge

Project description

Vorak: Vulnerability Oriented Red-teaming for AI Knowledge

PyPI version License Python Version

Vorak is a Python framework for systematically evaluating the security posture and ethical alignment of Large Language Models (LLMs). It enables adversarial testing, automated red-teaming, and structured vulnerability assessments to help researchers, developers, and enterprises identify and mitigate risks in generative AI systems.


Table of Contents


Features

  • LLM-Powered Evaluation – Leverages evaluator LLMs to classify, score, and explain model behavior.
  • Multi-Provider Support – Compatible with Gemini, OpenRouter, Anthropic, OpenAI, and custom APIs.
  • Adversarial Prompt Libraries – Run curated or custom adversarial test suites at scale.
  • Batch & Automated Testing – Evaluate multiple models, prompts, or categories in a single run.
  • Risk & Alignment Reporting – Export structured outputs as PDF, JSON, or CSV for audits and dashboards.
  • Interactive Web UI – Streamlit-powered sandbox for interactive testing and visualization.

Installation

Install the latest release from PyPI:

pip install vorak

For development setup (cloning and local installation):

git clone https://github.com/ruchirk22/vorak.git
cd vorak
pip install -r requirements.txt
pip install -e .

Quick Start

For help regarding all commands:

vorak evaluate --help

Run a single prompt evaluation:

vorak evaluate --model "openrouter/google/gemma-2-9b-it:free" --prompt-id "JBR_001"

Run a batch evaluation across categories:

vorak batch-evaluate --category "Jailbreaking_Role-Playing" \
    --model "gemini-1.5-flash-latest" \
    --output-json results.json

Configuration

Vorak uses environment variables for model provider authentication. Create a .env file in the project root:

GEMINI_API_KEY=your_gemini_api_key
OPENAI_API_KEY=your_openai_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key

Usage

Command-Line Interface

View available commands:

vorak --help

Web Interface

Launch the interactive Streamlit UI:

streamlit run vorak/web_interface/Home.py

Project Structure

vorak/               # Core framework
  ├── cli.py         # CLI entrypoint
  ├── agents/        # Attack agents
  ├── core/          # Evaluators, connectors, analyzers
  ├── prompts/       # Prompt libraries
  └── web_interface/ # Streamlit-based UI

.tests/              # Unit tests
.github/workflows/   # CI/CD configs
pyproject.toml       # Build configuration
requirements.txt     # Dependencies
CONTRIBUTING.md      # Contribution guidelines
LICENSE              # License
README.md            # Documentation

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.


License

Vorak is licensed under the Apache 2.0 License.


Citation

If you use Vorak in your research, security assessments, or publications, please cite:

@software{vorak,
  author       = {Ruchir Kulkarni},
  title        = {Vorak: Vulnerability Oriented Red-teaming for AI Knowledge},
  year         = {2025},
  publisher    = {PyPI},
  url          = {https://pypi.org/project/vorak/}
}

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