jabir-khan/hunter-llm-sft-v1
HunterLLM SFT v1 Instruction + preference dataset for training a bug-bounty / offensive-security assistant that thinks like a red-teamer, prioritizes attacker primitives and reachable impact, and writes triager-friendly reports — strictly scoped to authorized engagements (bug bounty programs, contracted pentests, isolated labs). Files File Rows Schema sft_train.jsonl ~33.1k {instruction, input, output, tags, meta} dpo_pairs.jsonl ~33.1k {prompt… See the full description on the dataset page: https://huggingface.co/datasets/jabir-khan/hunter-llm-sft-v1.
HunterLLM SFT v1
Instruction + preference dataset for training a bug-bounty / offensive-security assistant that thinks like a red-teamer, prioritizes attacker primitives and reachable impact, and writes triager-friendly reports — strictly scoped to authorized engagements (bug bounty programs, contracted pentests, isolated labs).
Files
Sources (raw)
GitHub repos used
OWASP/CheatSheetSeries, OWASP/wstg, OWASP/ASVS, OWASP/owasp-mastg, OWASP/API-Security, OWASP/Top10, swisskyrepo/PayloadsAllTheThings, swisskyrepo/InternalAllTheThings, danielmiessler/SecLists (filtered), projectdiscovery/nuclei-templates, rapid7/metasploit-framework (docs only), reddelexc/hackerone-reports (indexes only), nahamsec/Resources-for-Beginner-Bug-Bounty-Hunters, jhaddix/tbhm, Hari-prasaanth/Web-App-Pentest-Checklist, harshinsecurity/web-pentesting-checklist, dwisiswant0/awesome-oneliner-bugbounty, infoslack/awesome-web-hacking, EdOverflow/bugbounty-cheatsheet, ngalongc/bug-bounty-reference, Ignitetechnologies/Mindmap, 0xInfection/Awesome-WAF, bugcrowd/vulnerability-rating-taxonomy, devanshbatham/Awesome-Bugbounty-Writeups, kh4sh3i/Bug-Bounty-Writeups, qazbnm456/awesome-web-security.
Writeup URL hosts
portswigger.net (Research blog), googleprojectzero.blogspot.com, blog.doyensec.com, research.nccgroup.com, bishopfox.com, posts.specterops.io, blog.assetnote.io, labs.detectify.com, blog.detectify.com, projectdiscovery.io, github.blog, snyk.io, www.acunetix.com, owasp.org.
Instruction synthesis
Per-source specialized templates produce diverse training signals:
- GitHub generic:
hunt_plan,code_review,report_draft. - GitHub specialized: Metasploit module → exploitation + proof-of-impact + adjacent surfaces. HackerOne report-index row → infer primitive + hunt strategy
- report skeleton. Nuclei template → matcher analysis + weaponization + adjacent templates. OWASP doc → focused triple-template.
- NVD CVE: three templates per CVE —
triage(offensive root cause),hunt(fingerprint + evidence),report(HackerOne-style skeleton). - CISA KEV: "actively-exploited" priority framing with vendor/product fingerprinting and severity uplift narrative.
- MITRE ATT&CK: TTP → offensive operator framing (kill-chain phase, evidence, defender telemetry to expect).
- URL writeups: offensive distillation of research posts (attacker playbook + impact stack + replay strategy).
Every instruction carries the AUTHORIZATION_NOTE so the model learns to keep work scoped to authorized targets.
Curation pipeline
- Quality scoring penalizes config/build files, short or low-prose inputs, pure YAML/key-value blobs.
- MinHash LSH deduplication at threshold 0.85 (datasketch).
- Tag inference on bug-class keywords — XSS, SQLi, RCE, SSRF, XXE, Deserialization, OAuth, GraphQL, PathTraversal/LFI/RFI, CSRF, CSP, CORS, IDOR, etc.
DPO pair synthesis
For each curated SFT row we keep the original output as chosen and synthesize a deliberately weaker / over-cautious rejected response, training the model to prefer concrete attacker-primitive reasoning over generic defensive boilerplate.
Intended use
- Fine-tuning small/mid open LLMs (Llama-3-8B-Instruct, Mistral-7B-Instruct, DeepSeek-Coder, etc.) for bug-bounty mentoring, report drafting, and attacker-primitive analysis on authorized targets.
- Not intended for unauthorized testing, weaponization against third parties, or evasion of program rules.
Limitations & known biases
- HackerOne report titles are public metadata only; the dataset does not contain disclosed report bodies.
- Public writeup extraction is best-effort (some sites JS-render or block scrapers); failed URLs are silently skipped.
- Quality filter is heuristic; a small fraction of low-signal rows remain.
- Built on a single NVD lookback window — extend with
hunter-llm collect-nvd --years Nfor longer coverage. - CISA KEV uses templated short descriptions; MinHash dedup drops ~70% of entries as near-duplicates by design (the 482 surviving rows still represent the breadth of vendor/product/CVE primitives).
Reproducibility
Generated by HunterLLM:
hunter-llm bootstrap-data --skip-trickest --full \
--urls data/urls/writeups.txt
# Or piecewise:
hunter-llm collect-github --skip-trickest
hunter-llm collect-nvd --years 3
hunter-llm collect-cisa-kev
hunter-llm collect-mitre-attack
hunter-llm collect-urls data/urls/writeups.txt
hunter-llm build-dataset
hunter-llm export-dpoLicense
CC-BY-SA-4.0, matching the most restrictive permissive source license in the mix (OWASP). Underlying sources retain their respective licenses; provenance is preserved in meta.
