A large cybersecurity dataset can still be difficult to use well if its examples blur source material with repeated context. HolyCyber makes that distinction visible: its records include provenance and mark reference appendices, so users can inspect or exclude material that is not central to the topic being taught.
What Sets It Apart
- Each of 51,805 records is at least 2,000 tokens and follows a three-turn chat format, making the collection suited to long-form instruction tuning rather than short fact retrieval.
- Its 17 layers cover defensive security areas including detection engineering, incident response, vulnerability management, and AI/ML security, allowing domain-focused selection.
- Stable row keys, measured token counts, source references, and group-based train/validation/test splits support filtering and reproducibility.
- The dataset explicitly reports that 77.5% of rows contain a labelled reference appendix. This transparency helps users mask reused context, but also means the full record is not always devoted to its named entity.
Great Fit If…
Great fit if you are building or evaluating a defensive cybersecurity assistant and need long, source-traceable examples that can be filtered by domain. Look elsewhere if you need expert-reviewed examples, short Q&A pairs, non-English data, or a single uniform licence: the collection is pipeline-built rather than reviewed row by row, is English-only, and inherits differing licences from its source materials.
