DrugHub-scrape / README.md
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Add listing_enrichment (typesafe/jev-1.13 labels, 19 Sep 2026) and README section
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metadata
pretty_name: DrugHub Market Snapshot (September 2026)
license: cc-by-nc-sa-4.0
language:
  - en
size_categories:
  - 100K<n<1M
tags:
  - darknet
  - marketplace
  - drug-policy
  - measurement
  - reviews
configs:
  - config_name: listings
    data_files: listing_pages.parquet
  - config_name: shipping_options
    data_files: shipping_options.parquet
  - config_name: bulk_options
    data_files: bulk_options.parquet
  - config_name: vendors
    data_files: vendor_pages.parquet
  - config_name: reviews
    data_files: reviews.parquet
  - config_name: vendor_pgp_keys
    data_files: vendor_pgp_keys.parquet
  - config_name: vendor_listing_titles
    data_files: vendor_listing_titles.parquet
  - config_name: rosters
    data_files: rosters.parquet
  - config_name: roster_entries
    data_files: roster_entries.parquet
  - config_name: category_counts
    data_files: category_counts.parquet
  - config_name: category_count_entries
    data_files: category_count_entries.parquet
  - config_name: fetch_log
    data_files: fetch_log.parquet
  - config_name: listing_enrichment
    data_files: listing_enrichment.parquet

DrugHub Market Snapshot, September 2026

A complete, text-only capture of the public listing, vendor, and review pages of DrugHub, a Monero-only darknet market operating since 2023. Everything here was visible to any visitor without an account. Doesn't include any images.

Collected 16-17 September 2026. Enriched with model-derived labels (typesafe/jev-1.13) on 19 September 2026; see the listing_enrichment table and the Enrichment section below.

What's in it

Table Rows Description
listings 22,621 One row per listing page: title, category, description, refund policy, prices, stock, shipping, unit, minimum order, vendor stats as shown on the listing.
shipping_options 57,982 Shipping methods per listing with XMR and fiat prices.
bulk_options 82,135 Bulk price tiers per listing.
vendors 9,418 One row per vendor page fetched (profile plus each review page). Profile stats, seven average ratings, about text. Filter page_r = 0 for one row per vendor (1,598).
reviews 423,003 Every review on the site: listing title, date, and seven percentage scores.
vendor_pgp_keys 1,676 PGP public keys as published on vendor profiles.
vendor_listing_titles 35,793 Every listing title each vendor has been reviewed on, including delisted ones.
rosters, roster_entries 91 / 145,422 Snapshots of the sidebar vendor roster with feedback percentages, deduplicated by content.
category_counts, category_count_entries 16 / 1,888 Snapshots of the category tree with listing counts.
listing_enrichment 22,621 Model-derived labels per listing (language, substance, form, purity claim, and 12 other fields). See "Enrichment" below.
fetch_log 35,402 Every HTTP fetch made, including failures, with timestamp, status, and content hash. Page bodies are not included.

Every parsed row carries a fetch_id that points into fetch_log, and a fetched_at unix timestamp.

Coverage

  • Listings: 22,621 of the 22,641 discovered; the other 20 were removed by the site during the crawl. 434 are digital goods with no shipping destination.
  • Vendors: 1,598 of 1,601 on the roster; 3 profiles returned 404.
  • Reviews: all review pages of all vendors, July 2023 to 17 September 2026. 1,416 vendors have at least one review.

Listings by category

Category Listings Subcategories
Drugs 20,429 67
Forgeries / Counterfeits 1,540 4
Services 415 11
Software 228 5
Defense / Counter Intel 9 4

Largest subcategories: Prescription Drugs (3,080), Cannabis - Buds and Flowers (3,079), Steroids (1,353), Benzos - Pills (1,337), Stimulants - Cocaine (964), Watches (838), Dissociatives - Ketamine (794), Psychedelics - LSD (617).

Shipping origins are led by the United States (6,093), United Kingdom (4,286), India (2,616), Germany (2,216), China (1,897), and Australia (1,267). Prices are quoted in XMR plus one of USD, EUR, GBP, AUD, or CAD; the site's own exchange rates at fetch time are on every row (xmr_usd, xmr_eur, ...).

Reviews by year

Year Reviews
2023 23
2024 12,515
2025 150,520
2026 (to 17 Sep) 259,945

Things to know before using it

  • Prices are as displayed. Nothing has been converted. Use the per-row exchange rates or your own historical series.
  • Reviews have no identifier and no text. They are numeric scores plus a date, listed newest first. Their position on a page can shift as new reviews arrive, so a small number may be duplicated across page boundaries. Reviews with identical (vendor, listing title, date, scores) are common and mostly genuine; the data has not been deduplicated.
  • Reviews reference listing titles, not ids. Joining on (vendor, title) matches about 63% of reviews to a current listing. The rest are on delisted, renamed, or private listings.
  • Relative dates are stored as shown ("21 months ago", "Today"). Resolve them against fetched_at.
  • vendors is one row per page, so profile stats repeat across a vendor's review pages. Filter page_r = 0 unless you want the review pages.
  • Vendor ratings are near-uniform (80% of vendors at 98-100%). Cancellation and dispute counts carry more signal.
  • Free text is raw. Descriptions keep their original line breaks and any decorative characters. The site enforces a 50-character minimum and roughly a 10,000-character maximum.
  • Category is the market's own tree, not a normalised taxonomy. About 10% of listings are outside the Drugs category.

Enrichment (model-derived, not ground truth)

listing_enrichment holds one row per listing with labels produced by typesafe/jev-1.13, a classification-only model that picks from options we define and returns a probability distribution. Every enumeration includes an escape option (other_listed_class, not_stated, unknown, ...), and each choice column has a companion <field>_p with the probability of the chosen option. answers_json carries the full distributions. Treat these as annotations to be thresholded, not facts.

Field Type What it answers
language choice Primary language of the description (ISO code, mixed, other, unknown)
substance choice Substance sold, from a per-subcategory vocabulary (Drugs only)
product_type choice Product kind for non-drug categories
form choice Physical form (pill, powder, crystal, flower, vape, blister_pack, ...)
purity_claim choice Stated purity/potency bucket (none, under_50, 50_79, 80_94, 95_plus)
lab_tested 0-1 Claims lab testing
pharma_claim choice Presented as genuine pharmaceutical, replica/pressed, or not applicable
counterfeit_risk 0-1 Imitates a pharmaceutical product (branded press, fake blister, RC substitution)
quantity_stated choice Whether the price maps to a stated quantity
wholesale 0-1 Bulk/wholesale orientation
stealth_described 0-1 Packaging/stealth described
tracking choice Tracked, untracked, both, not stated
fe_required 0-1 Vendor asks for Finalize Early / early escrow release
external_contact choice Mentions an outside channel (see caveat)
cross_market 0-1 Mentions history on another darknet market
harm_reduction 0-1 Contains dosing guidance or safety warnings
fentanyl_mention choice none, claims_free, contains, warning
text_style choice terse, handwritten, marketing, template, other

Notes:

  • prompt_version is 2 for most rows and 3 for Prescription Drugs, Peptides, Steroids, and Benzos - Pills, where the substance vocabulary was expanded after a first pass. All other questions are identical across versions.
  • substance vocabularies were built from title-token frequencies per subcategory. Prescription Drugs uses therapeutic-class buckets for the long tail; about 12% of that subcategory still lands in other_listed_class.
  • external_contact has low precision: its other_platform value often reflects a mention of another site or market rather than an actual handle.
  • The model saw the title, category, unit, origin, and the first 2,500 characters of the description.