Generative AIs, especially Large Language Models (LLMs) such as ChatGPT or Llama, have advanced significantly, positioning them as valuable tools for digital forensics. While initial studies have explored the potential of ChatGPT in the context of investigations, the question of to what extent LLMs can assist the forensic report writing process remains unresolved. To answer the question, this article first examines forensic reports with the goal of generalization (e.g., finding the `average structure' of a report). We then evaluate the strengths and limitations of LLMs for generating the different parts of the forensic report using a case study. This work thus provides valuable insights into the automation of report writing, a critical facet of digital forensics investigations. We conclude that combined with thorough proofreading and corrections, LLMs may assist practitioners during the report writing process but at this point cannot replace them.

翻译：生成式人工智能，特别是像ChatGPT或Llama这样的大型语言模型（LLMs），已取得显著进展，使其成为数字取证领域有价值的工具。虽然初步研究已探索了ChatGPT在调查中的应用潜力，但LLMs能在多大程度上辅助取证报告写作过程的问题仍未得到解答。为回答这一问题，本文首先以泛化（例如寻找报告的“平均结构”）为目标对取证报告进行考察。随后，我们通过案例研究评估了LLMs在生成取证报告不同部分时的优势与局限性。因此，本研究为报告写作自动化——数字取证调查的关键方面——提供了宝贵的见解。我们得出结论：结合彻底的校对与修正，LLMs可在报告写作过程中协助从业人员，但目前阶段尚无法取代他们。