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dig-through-data-brokerslisted

Use people-search aggregators and primary public records to find addresses, phone numbers, relatives, age and background on a person, and to audit and remove your own exposure. Covers Spokeo, BeenVerified, Whitepages, TruePeopleSearch, FastPeopleSearch, That'sThem, Radaris, Intelius and Pipl, plus voter files and county court and property records. Use when running a people search or reverse address lookup, tracing a debtor or missing person, building a subject's address history, or removing yourself from broker sites. Applies to skip tracing and debt recovery, asset investigation, executive protection, and personal exposure audits. Explains the FCRA limits that bar broker data from employment, tenancy, insurance and credit decisions, and the GDPR position. Reference at useosint.com/skills/dig-through-data-brokers.
useosint/osint-skills · ★ 16 · Data & Documents · score 78
Install: claude install-skill useosint/osint-skills
# Dig through data brokers People-search sites resell a blend of public records, marketing data, and self-reported data. They are fast, cheap lead generators and terrible evidence. The one rule that matters: **a broker record is a lead, never a fact.** Confirm every field you intend to use against the primary source the broker got it from — and if you cannot identify that primary source, do not use the field. ## What these services actually are Three input streams, blended and sold: - **Public records** — property deeds, court filings, business registrations, voter files where public, professional licences, bankruptcy, marriage and divorce. Authoritative at origin; the broker's copy is a stale transcription. - **Marketing and commercial data** — warranty cards, loyalty programmes, subscriptions, credit-header data, online forms, ad exchanges. Never verified, often inferred, frequently household-level rather than person-level. - **Self-reported and scraped** — profiles, résumés, forum posts, and whatever the broker's own users typed in. They also buy from each other, constantly. That is the most important structural fact about the category: one wrong record propagates across every brand, and cross-checking five brokers gives you five copies of one error wearing five hats. Apparent corroboration across brokers is worth close to nothing. ## Why the data is wrong - **Address history is append-only in practice.** Brokers add addresses and rarely retire them, so