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DATASET_CARD.md

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+# HolyCyber — Dataset Card
+
+A large, fully grounded, decontaminated instruction dataset spanning cybersecurity.
+
+## Overview
+
+- **Rows:** 51,805
+- **Groups (leakage units):** 12,125
+- **Splits:** test=5,702, train=40,998, val=5,105
+- **Domains:** 17  |  **Task types:** 19
+- **Avg assistant length:** 11,001 chars
+- **Row size (tiktoken cl100k, user+assistant):** min 2,050 / median 2,324 / mean 2,464 / p90 2,926 / max 6,790 tokens
+- **Total tokens:** 127,643,325  |  **Rows below the 2,000-token floor:** 0
+- **Seed:** 1337  |  **Canary:** `BENCHMARK DATA SHOULD NEVER APPEAR AS TRAINING DATA: HOLYCYBER-DECONTAM-CANARY-9f2c7a14`
+- **Entity's own material:** median 16% of an answer's tokens; 32,399 rows are below 25%. The balance is the labelled reference appendix (`## Reference: ...`), not extra facts about the row's entity.
+
+## Record format
+
+One JSON object per line; `messages` is a three-turn chat (system / user / assistant).
+
+```json
+{"id": "6d408e38f3cb8dff", "row_key": "detection_engineering:attack:T1568:detection_engineering:detection_strategy:1",
+ "domain": "detection_engineering",
+ "subdomain": "detection_strategy", "task_type": "detection_engineering",
+ "difficulty": "advanced", "group_key": "attack:T1568", "source": "mitre-attack",
+ "license": "...", "split": "train", "canary": "...",
+ "tokens": {"user": 180, "assistant": 2350, "total": 2530},
+ "core_share": 0.41, "appendix": true,
+ "references": [{"title": "...", "url": "https://..."}],
+ "messages": [{"role": "system", "content": "..."},
+              {"role": "user", "content": "..."},
+              {"role": "assistant", "content": "## ...\n..."}]}
+```
+
+| Field | Meaning |
+|---|---|
+| `id` | content hash of user+assistant, stable across rebuilds of the same row |
+| `row_key` | stable identity across rebuilds (`domain:group:task:subdomain:part`) |
+| `domain` / `subdomain` | the layer, and the slice of it the row covers |
+| `task_type` | the question shape (detection, mitigation, mapping, response, ...) |
+| `difficulty` | derived from the task shape, not guessed |
+| `group_key` | the source entity; the unit of the train/val/test split |
+| `source` / `license` | the authoritative source, and its licence |
+| `tokens` | measured `cl100k_base` counts for user, assistant and total |
+| `core_share` | share of the answer that is the entity's own material (1 - appendix) |
+| `appendix` | whether the row carries a `## Reference:` appendix |
+| `references` | resolvable links for the entities cited in the answer |
+| `canary` | decontamination marker |
+
+## What a row contains
+
+Section headings used in the answers (appendix excluded):
+
+| Section | Rows |
+|---|---|
+| Summary | 26,919 |
+| Detection strategies and analytics | 7,440 |
+| Mitigations | 6,854 |
+| Tracked users (groups, malware, tools) | 6,836 |
+| Classification | 5,088 |
+| Introduction | 3,499 |
+| Platforms | 3,123 |
+| Background | 2,807 |
+| Associated weaknesses | 2,379 |
+| Scope note | 2,283 |
+| What it is | 2,281 |
+| Detection logic | 2,249 |
+| Engineering note | 2,249 |
+| Supports technique(s) | 2,232 |
+| Telemetry | 2,210 |
+
+## Row design
+
+The corpus is built as **one focused dataset per cybersecurity domain** (`dataset/layers/<domain>/`), each from that domain's own authoritative sources, and this global file is their concatenation.
+
+Each row is a **self-contained, long-form briefing on one entity** (an ATT&CK technique/group/software, a CWE weakness, a CAPEC pattern, a KEV vulnerability, a Sigma rule, an ATLAS technique, a D3FEND control, or a section of a cited arXiv paper). A row is built in three steps:
+
+1. **Base cell** — the parser output for that entity and that (task type, subdomain).
+2. **Task shapes** — the same entity asked a *different* defensive question (detection, mitigation, framework mapping, response, adversary usage), built only from other sections of that entity's own record, so no new fact is introduced.
+3. **Reference pack** — if the row is still short, it is topped up with compact descriptions of other entities *of the same domain*, taken from that domain's own source text, with a rotating window so two rows do not carry identical padding.
+
+Rows are packed to a hard floor of 2,000 tokens, so **no row is below the floor**. Context is allocated **disjointly** across an entity's cells, so a record is never repeated inside a single entity, and the split is cut on `group_key` so an entity never appears in two splits.
+
+## Construction
+
+Sources are parsed deterministically; no facts are invented by a model.
+
+| Source | Rows | Licence |
+|---|---|---|
+| mitre-attack | 27,221 | MITRE ATT&CK — free for defensive use |
+| arxiv-corpus | 11,332 | arXiv preprints; cited per row |
+| cisa-kev | 5,843 | CISA KEV — U.S. Government work (public domain) |
+| cwe | 2,747 | CWE (MITRE) — attribution required |
+| capec | 2,714 | CAPEC (MITRE) — attribution required |
+| ietf-rfc | 645 | see source |
+| atlas | 608 | MITRE ATLAS — free for defensive use |
+| nist-publication | 432 | see source |
+| owasp-cheatsheet | 175 | see source |
+| research-corpus | 88 | Curated; cites public arXiv preprints |
+
+## Quality controls
+
+- **Exact duplicates removed:** 0
+- **Near-duplicates removed:** 952 (MinHash-LSH: 5-word shingles, 112 perms, Jaccard >= 0.9; same task type only)
+- **Decontamination:** token-25 overlap vs 27 benchmark files; 2,064 benchmark CVE IDs excluded; canary GUID emitted per row
+- **Contaminated rows removed:** 0 ({})
+- **Quality gate:** 315 rejected ({})
+- **Split integrity:** group-level by `group_key`; no group appears in more than one split
+
+## Domain coverage
+
+| Domain | Rows | Subdomains covered |
+|---|---|---|
+| detection_engineering | 7,970 | 6 |
+| ai_ml_security | 4,602 | 10 |
+| vulnerability_management | 3,493 | 4 |
+| governance_risk | 3,176 | 5 |
+| defense_engineering | 2,986 | 3 |
+| incident_response | 2,943 | 4 |
+| attack_knowledge | 2,887 | 6 |
+| threat_intelligence | 2,865 | 6 |
+| pentest | 2,788 | 7 |
+| secure_coding | 2,659 | 6 |
+| network_security | 2,373 | 5 |
+| identity_access | 2,304 | 4 |
+| cloud_security | 2,244 | 5 |
+| safety_boundary | 2,200 | 5 |
+| ml_security_methodology | 2,111 | 6 |
+| malware_analysis | 2,104 | 4 |
+| cryptography | 2,100 | 5 |
+
+**Known coverage gaps (subdomains not yet populated):**
+
+- threat_intelligence: malware, procedure
+- vulnerability_management: prioritisation, weakness_consequences, weakness_detection, weakness_mitigation
+- detection_engineering: false_positive_analysis
+- defense_engineering: architecture_control, hardening
+- incident_response: eradication, lessons_learned, recovery
+- network_security: exfiltration
+- cloud_security: storage_exposure
+- malware_analysis: aliases, static_indicators
+- identity_access: kerberos, mfa_bypass
+
+## Intended use
+
+Supervised fine-tuning / instruction tuning of a defensive cybersecurity assistant (HolyCyber persona). All rows are defensive or detection/analysis oriented.
+
+## Out of scope
+
+No functional exploits, malware, weaponised jailbreak prompts, or operational attack tooling. Pentest rows are framed as authorised engagements; offensive concepts are conceptual and paired with detection/remediation.
+
+## Limitations
+
+Rows are unique; some paragraphs are not. The framework domains complete short entity records with a labelled reference appendix, so a sizeable share of their answer tokens is reused material from the same domain. `research/AUDIT_REPORT.md` measures the paragraph reuse, including how much of it crosses the train/test boundary, and `research/EXTERNAL_REVIEW.md` records how this compares with a public peer dataset.
+
+No row has been reviewed individually by a domain expert: grounding bounds invention, it does not by itself prove correctness.