A high‑quality, SlimPajama‑style corpus distilled from the HackTricks knowledge base (core wiki and, optionally, HackTricks Cloud). Each record corresponds to a cleaned Markdown article with headings preserved, code fences kept, and rich provenance metadata for reproducible research and downstream retrieval.

Token count: ~2.75M tokens.

⚠️ Ethical use only. This corpus is intended for lawful research, education, and defensive security. Do not use it to violate terms of service or applicable laws.

What’s in this release (Parquet)

Primary delivery = Parquet shards under data/hacking_tricks/.../train-*.parquet (Hub‑managed) for fast streaming with 🤗 datasets.
Raw JSONL retained at raw/hacking-tricks.jsonl[.gz|.zst] for transparency and reproducibility.
Named config: hacking_tricks (single config; no all config).

Highlights

Clean, article‑level records suitable for pretraining/continued‑pretraining, RAG, and eval.
Code blocks preserved (fenced code kept as‑is) while removing front‑matter/boilerplate.
Provenance: repo, commit, path, GitHub blob URL, and a best‑effort canonical site URL per article.
Lightweight schema: {"text": ..., "meta": {...}} with stable keys for training and retrieval.

Dataset layout

/                           # dataset root (this README)
  raw/
    hacking-tricks.jsonl    # original export (optionally .gz/.zst)
  data/
    hacking_tricks/
      default/1.0.0/train/
        train-00000-of-XXXX.parquet
        train-00001-of-XXXX.parquet
        ...

Depending on future pushes, you may also publish separate configs (hacktricks_core, hacktricks_cloud). This card documents the current single hacking_tricks config.

Schema

Each row is a UTF‑8 JSON object with the following structure (identical for Parquet features):

{
  "text": "<cleaned article markdown with code fences>",
  "meta": {
    "source": "HackTricks (git)",
    "source_repo": "https://github.com/HackTricks-wiki/hacktricks",
    "repo_branch": "master",
    "repo_commit": "<git-sha>",
    "source_path": "path/in/repo/file.md",
    "source_url_github": "https://github.com/.../blob/<sha or branch>/path.md",
    "source_url_site": "https://book.hacktricks.wiki/<page>",
    "title": "<article title>",
    "section_titles": ["H1/H2/H3…"],
    "n_chars": 12345,
    "n_words": 2345,
    "sha256": "<content-hash>",
    "crawl_ts": "2025-11-04T00:00:00+00:00",
    "lang": "en",
    "license": "CC BY-NC-SA 4.0 (per upstream repo)"
  }
}

Field notes

text keeps fenced code blocks and normalized headings. Front‑matter is removed.
source_url_site is a best‑effort canonical link to the rendered wiki page; source_url_github always points to the exact file/commit.
license mirrors the upstream license hint for clarity.

Quickstart (🤗 Datasets)

Load the Parquet config (recommended)

from datasets import load_dataset

REPO = "tandevllc/hacking-tricks"
ds = load_dataset(REPO, name="hacking_tricks", split="train")
print(len(ds), ds[0]["meta"]["title"])  # sample

Direct JSONL loading from `raw/` (explicit)

from datasets import load_dataset

ds = load_dataset(
    "json",
    data_files="raw/hacking-tricks.jsonl",
    repo_id="tandevllc/hacking-tricks",
    split="train",
)

Typical filters

# Long English articles only
long_en = ds.filter(lambda r: r["meta"].get("lang") == "en" and r["meta"].get("n_words", 0) > 800)

# Articles with code (simple heuristic)
with_code = ds.filter(lambda r: "```" in (r["text"] or ""))

# Slice by section heading keyword
ad_ops = ds.filter(lambda r: any("Active Directory" in h for h in r["meta"].get("section_titles", [])))

RAG‑ready retrieval columns

meta.source_url_github — stable pointer to the exact file.
meta.source_url_site — user‑friendly URL for UI previews.
meta.sha256 — robust dedup key across updates.

Intended uses

Pretraining / Continued pretraining for security‑aware models.
RAG / QA over a curated set of red‑team/blue‑team encyclopedic pages.
Summarization & explanation of workflows, checklists, and attack surfaces.
Evaluation: security knowledge, long‑form reasoning on procedures, and code‑aware contexts.

This corpus is didactic/encyclopedic. It does not replace hands‑on lab data, exploit PoCs, or live telemetry.

Cleaning & quality

YAML front‑matter and boilerplate removed; headings normalized; excessive blank lines collapsed.
Code fences retained verbatim for downstream code‑aware models.
Article‑level minimum length applied (very short files excluded).
Stable dedup via meta.sha256 and exact source_path at a specific commit.

Limitations & caveats

Upstream drift: HackTricks evolves; future updates may add/rename pages.
License constraints: Non‑commercial, ShareAlike terms apply; see License below.
Context gaps: Some pages assume prior knowledge or external links.
No execution traces: Articles describe tactics; they are not runtime logs or CVE feeds.

License

Underlying content: © respective HackTricks authors, typically CC BY‑NC‑SA 4.0 as stated in the upstream repositories/site.

When you use this dataset, you must:

Provide attribution to HackTricks and the specific article(s) used.
Use it non‑commercially unless you have additional permission from rights holders.
Distribute derivatives under the same license (ShareAlike).

If you are a rights holder and would like a page revised or removed, please open an issue on the dataset page or email the maintainer.

Citation

If this dataset helps your research, please cite it alongside HackTricks:

@dataset{tandevllc_2025_hacktricks_slimpajama,
  author = {Gupta, Smridh},
  title  = {HackTricks SlimPajama Corpus},
  year   = {2025},
  url    = {https://huggingface.co/datasets/tandevllc/hacking-tricks}
}

You should also attribute individual HackTricks pages used (e.g., in an acknowledgments section) to satisfy CC BY‑NC‑SA 4.0.

Maintainer

Smridh Gupta — smridh@tandev.us

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HackTricks SlimPajama Corpus (Parquet)