Jailbreak techniques for large language models (LLMs) evolve faster than benchmarks, making robustness estimates stale and difficult to compare across papers. This article introduces JAILBREAK FOUNDRY (JBF), a system that translates jailbreak papers into executable modules through a multi-agent workflow for unified evaluation.
JBF consists of three core components:
- JBF-LIB for shared contracts and reusable utilities.
- JBF-FORGE for multi-agent paper-to-module translation.
- JBF-EVAL for standardizing evaluations.
Across 30 reproduced attacks, JBF achieves high fidelity with a mean reproduced-reported attack success rate (ASR) deviation of +0.26 percentage points. By leveraging shared infrastructure, JBF reduces attack-specific implementation code by over half, achieving an 82.5% mean reused-code ratio compared to original repositories.
This system enables a standardized AdvBench evaluation of all 30 attacks across 10 victim models using a consistent GPT-4o judge. By automating both attack integration and standardized evaluation, JBF provides a scalable solution for creating living benchmarks that keep pace with the rapidly shifting security landscape.
Blogger's Review: The emergence of JBF represents a significant advancement in the security domain, transforming research findings into actionable modules and greatly enhancing the standardization of attack evaluations. This approach not only improves reproducibility but also provides powerful tools for future research, making it a noteworthy development to watch and promote.