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CLUSTER AUTOMATION-BYPASSES-CHECKS · 3 ENTRIES · EARLIEST ENTRY 2026-01-02

Fraudulent discount automation toolkits

This cluster consists of automation toolkits that bypass identity verification checks to fraudulently obtain student, teacher, and military discounts on subscription services. The dated entry history is too thin (only 3 dated entries) to read a shape from; the cluster predates the index or its members are undated. Among traction leaders, SheerID shows the highest activity signal with 1 star.

Entry timeline

ENTRY TIMELINE

JAN 2026: 3
JAN 2026

Each bar is the month a member carries, which is a creation date where the source published one and a crawl date otherwise. Nothing in the index was found before 11 August 2026, and coverage broadened sharply on 14–15 August, so a bar from then on reports how much we found that month, not how much was built; an earlier bar reports how far back a member's own source dated it — not how long we have been watching.

Members by activity

Activity signals, not revenue.

Build origin · 3 unlabelled

Operator · 3 hobby

Two labels per entry, never collapsed into one: how it was built, and who stands behind it. Counted over the 3 listed below. Unlabelled means nothing has decided yet — not that the answer is small.

  1. 01SheerID1★9 mostale—hobbyAutomation toolkit that bypasses identity verification checks to fraudulently obtain student, teacher, and military discounts on subscription services.
  2. 02SheerID-CURRY0★8 mostale—hobbyAutomation toolkit that bypasses identity verification checks to fraudulently obtain student, teacher, and military discounts on subscription services.
  3. 03Himanshuop0★9 mostale—hobbyAutomation toolkit that bypasses identity verification checks to fraudulently obtain student, teacher, and military discounts on subscription services.

Ranked by traction, highest first, and paged 20 at a time — this is a window on the cluster, never the whole of it. Ties are broken by a stable id so a product cannot appear on two pages or fall between them. Browse every cluster.