Jailbreak Llms | Awesome Repository

This project is a comprehensive ecosystem of frameworks, toolkits, and datasets designed to evaluate model vulnerabilities and analyze jailbreak patterns. It serves as an adversarial testing framework and research toolkit for measuring the effectiveness of safety guardrails in large language models.

The system includes a library of real-world prompt injection datasets harvested from social media to study bypass strategies. It provides specialized tools for semantic attack analysis and prompt visualization, allowing for the mapping of relationships between adversarial prompts to discover common attack patterns.

The toolkit covers model safeguard validation through API-based evaluations and metric-based success validation. It employs structural pattern analysis and vector-based semantic mapping to quantify vulnerabilities and identify unique characteristics within jailbreak strategies.

Features

Adversarial Robustness Testing - Provides a full framework for evaluating model security and stability through adversarial attack simulation.
Prompt Injection Techniques - Analyzes adversarial input patterns and prompt injection techniques harvested from real-world usage.
Jailbreak Research Toolkits - Provides a comprehensive collection of tools and datasets for analyzing how prompts bypass safety constraints.
Model Evaluation Frameworks - Provides a system for running model inference and validation against curated forbidden datasets.

Features

Adversarial Robustness Testing - Provides a full framework for evaluating model security and stability through adversarial attack simulation.
Prompt Injection Techniques - Analyzes adversarial input patterns and prompt injection techniques harvested from real-world usage.
Jailbreak Research Toolkits - Provides a comprehensive collection of tools and datasets for analyzing how prompts bypass safety constraints.
Model Evaluation Frameworks - Provides a system for running model inference and validation against curated forbidden datasets.