An Objective for Nuanced LLM Jailbreaks

This codebase implements the target prefix generation pipeline from our nuanced LLM jailbreaks paper. For a given user requests and victim LLM, the pipeline automatically generates and selects target prefixes. Replacing the original "Sure, here is ..." with these prefixes enables more nuanced jailbreak attacks.

[arXiv]

Pre-Generated Target Prefixes (Ready to Use)

We pre-generated target prefixes for commonly used jailbreak requests in AdvBench for users to directly use and evaluate. These prefixes are stored in the data folder. Note: The CSV files do not include the original jailbreak requests (i.e. missing the 'goal' column) to avoid directly hosting the original AdvBench dataset. Please run ```python recover_requests.py`` to recover the original jailbreak requests.

We processed 100 jailbreak requests in advance, including 50 curated by us and 50 from PAIR. For these requests, we considered four victim LLMs: llama-2, 3, 3.1, and Gemma-2.

Quick Start

1. Create conda environment (optional):

   conda create -n nuancedjb python=3.11
   conda activate nuancedjb
   pip install -r requirements.txt
   

2. Generating prefixes for Llama-3-8B:

   python pipeline.py \
      --config="./default_config.py" \
      --config.victim_model="meta-llama/Meta-Llama-3-8B-Instruct" \
      --config.input_csv="./input/demo_requests.csv" \
      --config.output_dir="./output" \
      --config.start_step=1
   

3. (Optional) Loading from an existing checkpoint and redo selection with a different weight for PASR:

   python pipeline.py \
      --config="./default_config.py" \
      --config.victim_model="meta-llama/Meta-Llama-3-8B-Instruct" \
      --config.input_csv="./input/demo_requests.csv" \
      --config.output_dir="./output" \
      --config.start_step=7 \
      --config.run_id={existing run id like ABCD}
   

Optional Arguments

Please refer to default_config.py for more optional arguments and their descriptions.

License

This repository is made available under a CC-by-NC license, however you may have other legal obligations that govern your use of other content, such as the terms of service for third party models.

Citation

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