Competition Report: Finding Universal Jailbreak Backdoors in Aligned LLMs
<|reference_start|>Competition Report: Finding Universal Jailbreak Backdoors in Aligned LLMs: Large language models are aligned to be safe, preventing users from generating harmful content like misinformation or instructions for illegal activities. However, previous work has shown that the alignment process is vulnerable to poisoning attacks. Adversaries can manipulate the safety training data to inject backdoors that act like a universal sudo command: adding the backdoor string to any prompt enables harmful responses from models that, otherwise, behave safely. Our competition, co-located at IEEE SaTML 2024, challenged participants to find universal backdoors in several large language models. This report summarizes the key findings and promising ideas for future research.<|reference_end|>
@article{rando2024competition,
    title={Competition Report: Finding Universal Jailbreak Backdoors in Aligned
  LLMs},
    author={Javier Rando and Francesco Croce and Kryv{s}tof Mitka and Stepan
  Shabalin and Maksym Andriushchenko and Nicolas Flammarion and Florian
  Tram`er},
    journal={arXiv preprint arXiv:2404.14461},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.14461},
    primaryClass={cs.CL cs.AI cs.CR cs.LG}
}