0.8.3

Jailbreak Evaluation Framework (JEF)

Full Documentation | 0din.ai

JEF is a CVSS-like scoring system for quantifying LLM jailbreak tactics. It provides a structured, repeatable framework for stack-ranking jailbreak methods based on their real-world efficacy and risk, scoring across three dimensions:

• Model Impact Radius — How many models and vendors are affected
• Retargetability — How flexibly the tactic applies across content categories
• Output Fidelity — How accurate and detailed the resulting outputs are

Installation

pip install 0din-jef

Quick Start

from jef import tiananmen, meth, nerve_agent, harry_potter

# Score against standardized benchmarks (0-100)
result = tiananmen.score("LLM response text")
result = meth.score("LLM response text")
result = nerve_agent.score("LLM response text")
result = harry_potter.score("LLM output", "reference text")

# Compute composite JEF score (0-10)
from jef import calculator
jef_score = calculator(num_vendors=3, num_models=7, num_subjects=2, scores=[80, 75])

Documentation

For the full framework methodology, scoring algorithm, complete usage guide, and API reference, visit the JEF Documentation.

Resources

• Blog: Quantifying the Unruly — A Scoring System for Jailbreak Tactics
• Overview: Jailbreak Evaluation Framework
• JEF Calculator
• Standardized Testing (0DIN Researcher Authentication Required)

Releases

Releases are managed through GitHub Releases and automatically published to PyPI.