by BishopFox · Agent Tool · ★ 158
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Broken Hill Broken Hill is a productionized, ready-to-use automated attack tool that generates crafted prompts to bypass restrictions in large language models (LLMs) using the greedy coordinate gradient (GCG) attack described in the "Universal and Transferable Adversarial Attacks on Aligned Language Models" paper by Andy Zou, Zifan Wang, Nicholas Carlini, Milad Nasr, J. Zico Kolter, and Matt Fredrikson. Broken Hill can generate robust prompts that successfully jailbreak LLMs configured differently than the one used to generate the prompts. For example: The same model with more or fewer parameters e.g. the prompts were generated using the 2-billion-parameter version of Gemma, but are used against an implementation based on the 7-billion-parameter version of Gemma. The same model with weights quantized to different types e.g. the prompts were generated using the version of Phi 3 with weights stored in format, but are used against the default version of Phi 3 that has the weights quantized to 4-bit integer format. The same model, but with different randomization settings e.g. a non-default temperature or random seed.
| Stars | 158 |
| Forks | 24 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 53.7203173499824/100 |
| Open Issues | 2 |
| Last Updated | 2024-12-18 |
| Created | 2024-07-25 |
| Platforms | python |
| Est. Tokens | ~325k |
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BrokenHill is A productionized greedy coordinate gradient (GCG) attack tool for large language models (LLMs). It is categorized as a Agent Tool with 158 GitHub stars.
BrokenHill is primarily written in Python.
You can find installation instructions and usage details in the BrokenHill GitHub repository at github.com/BishopFox/BrokenHill. The project has 158 stars and 24 forks, indicating an active community.
BrokenHill is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to BrokenHill on Agent Skills Hub include agent-skills, claude-forge, awesome-agent-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.