ForensicsData: A Digital Forensics Dataset for Large Language Models
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Abstract (arXiv)
The growing complexity of cyber incidents presents significant challenges for digital forensic investigators, especially in evidence collection and analysis. Public resources are still limited because of ethical, legal, and privacy concerns, even though realistic datasets are necessary to support research and tool developments. To address this gap, we introduce ForensicsData, an extensive Question-Context-Answer (Q-C-A) dataset sourced from actual malware analysis reports. It consists of more than 5,000 Q-C-A triplets. A unique workflow was used to create the dataset, which extracts structured data, uses large language models (LLMs) to transform it into Q-C-A format, and then uses a specialized evaluation process to confirm its quality. Among the models evaluated, Gemini 2 Flash demonstrated the best performance in aligning generated content with forensic terminology. ForensicsData aims to advance digital forensics by enabling reproducible experiments and fostering collaboration within the research community.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 13 of its 25 references that are in the map. First posted on arXiv 31 Aug 2025.
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References · 13
- 2023Enabling Large Language Models to Generate Text with Citationscited by 584
- 2024DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Datacited by 225
- 2024LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMscited by 142
- 2024LongCite: Enabling LLMs to Generate Fine-grained Citations in Long-context QAcited by 78
- 2024Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMscited by 73
- 2024CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligencecited by 61
- 2024CyberMetric: A Benchmark Dataset based on Retrieval-Augmented Generation for Evaluating LLMs in Cybersecurity Knowledgecited by 55
- 2024Data is all you need: Finetuning LLMs for Chip Design via an Automated design-data augmentation frameworkcited by 36
- 2024Can LLMs Speak For Diverse People? Tuning LLMs via Debate to Generate Controllable Controversial Statementscited by 33
- 2023HuntGPT: Integrating Machine Learning-Based Anomaly Detection and Explainable AI with Large Language Models (LLMs)cited by 25
- 2025Digital Forensics in the Age of Large Language Modelscited by 10
- 2023ChatGPT, Llama, can you write my report? An experiment on assisted digital forensics reports written using (Local) Large Language Modelscited by 8
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