  Openness is critical for the advancement of science. In particular, recent
rapid progress in AI has been made possible only by various open-source models,
datasets, and libraries. However, this openness also means that technologies
can be freely used for socially harmful purposes. Can open-source models or
datasets be used for malicious purposes? If so, how easy is it to adapt
technology for such goals? Here, we conduct a case study in the legal domain, a
realm where individual decisions can have profound social consequences. To this
end, we build EVE, a dataset consisting of 200 examples of questions and
corresponding answers about criminal activities based on 200 Korean precedents.
We found that a widely accepted open-source LLM, which initially refuses to
answer unethical questions, can be easily tuned with EVE to provide unethical
and informative answers about criminal activities. This implies that although
open-source technologies contribute to scientific progress, some care must be
taken to mitigate possible malicious use cases. Warning: This paper contains
contents that some may find unethical.
