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dig-through-data-brokers 标准

人肉搜索站点转售的是公共记录、营销数据与泄露数据的混合物——按这个结构去查。原文: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.

在 GitHub 打开

安装方式

cp -r skills/dig-through-data-brokers ~/.claude/skills/dig-through-data-brokers

把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同,Claude Code 默认是 ~/.claude/skills/

整仓一次性获取:git clone --depth 1 https://github.com/UseOSINT/Skills.git

依赖与权限

  • 无需 API Key
  • 无需联网
  • 依赖外部命令:go make
  • 以上为按正文与 frontmatter 自动推断的信号,仅供参考;安装前建议先阅读原文。
触发场景
running a people searchreverse address lookuptracing a debtormissing personbui

SKILL.md 正文

来源 UseOSINT/Skills@06243a5 · 许可 MIT · 内容未修改

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 a "current address" is often several moves old.

  • Household merging. Two people at one address, or two people with the same

name in one metro area, get fused into one profile. Same-name relatives —

father and son, cousins named for the same grandparent — merge constantly.

  • Relatives are inferred, not recorded. "Relatives" and "associates" lists are

usually address-co-occurrence: former roommates, landlords, and the previous

occupant show up as family.

  • Age is derived. Often from a birth year in a credit header or a voter file,

and often off by a year or displayed as a band.

  • Phone data ages fastest. Number portability and prepaid churn mean carrier

and line-type attributions decay quickly — see whose-number-is-this.

  • Corrections do not propagate. Getting one broker to fix a record does not

fix the upstream source or the six downstream buyers.

Triage: what to reach for first

What you holdBetter than a brokerUse a broker for
Name + cityLocal property and court records, voter file where publicGenerating a candidate address list to check against those records
Phone numberCarrier/line-type lookup via whose-number-is-thisReverse lookup to a candidate name, then confirm elsewhere
Email addresswhat-an-email-revealsReverse lookup to a candidate name
Name + need for relativesObituaries — far more accurate and they state the relationshipA first-pass household cluster to test against the obituary
Name + need for employmentProfessional networks, licensing boards, corporate registriesNothing. Broker employment data is the worst field they sell
Name + need for assetsProperty registry, court judgments, who-really-owns-itNothing usable
Your own name (self-audit)Nothing — brokers are the targetEnumerating your exposure before opting out

The honest summary: brokers are for turning a name into candidate selectors when

you have nothing else, and for auditing your own footprint. For every claim you

intend to publish or rely on, go to the primary record.

Method

  1. Anchor first. Do not run a bare name. Carry the disambiguating anchor from

find-anyone into every search, and treat any result that fails the anchor

test as a different person.

  1. Search a small number of brokers deliberately, not all of them. Pick ones

with different upstream sources rather than different brands.

  1. Extract selectors, not conclusions. You want candidate addresses, phones,

emails, middle names, age bands, and associated names. Each is a lead to test.

  1. Confirm each against a primary source. Address → property or court record.

Age → voter file, licensing record, or a document with a date of birth. Employment

→ the employer or a register. Relatives → an obituary or civil-registration index.

  1. Record which fields you confirmed and which you dropped. A broker field that

survived confirmation is now cited to the primary source, not to the broker.

  1. Pivot the confirmed selectors into the technique skills in the table below.

Primary-source catalogue by jurisdiction and record type, with access and legal

notes: [reference/source-catalogue.md](reference/source-catalogue.md).

The free-tier bait pattern

The business model is a teaser. Expect: a result page confirming a match exists

with characters masked; counts ("8 phone numbers, 12 addresses") designed to imply

depth; padding with public data the broker did not pay for; a progress animation

implying live searching that is actually a checkout funnel; a "report" that

arrives as an auto-renewing subscription with an awkward cancellation path; and

results for names that do not exist, because the funnel runs regardless.

Never treat a teaser count as evidence, and assume any paid tier bills until you

actively stop it. Some brokers do offer genuine investigator or business tiers

with contractual use restrictions — a different product, with obligations you

agree to when you sign.

FCRA and the rule that actually binds you (US)

In the US there is a legal line between two things that look identical:

  • A consumer reporting agency is regulated under the Fair Credit Reporting

Act. It must maintain accuracy procedures, give consumers access and dispute

rights, and only furnish reports for permissible purposes.

  • A data broker / people-search site is not a CRA, disclaims FCRA compliance

in its terms, and has none of those obligations.

The rule: **you must not use non-FCRA broker data to make decisions about

employment, tenancy, credit, or insurance.** That includes screening a job

applicant, vetting a tenant, or checking a contractor you are about to hire. If

the decision is one FCRA covers, you must go through a regulated CRA and follow

its process, including notice and adverse-action requirements. The broker's own

terms will say this; it is not decoration, and both the broker and the user have

been the subject of enforcement over it. This is the single most common way

otherwise-legitimate investigators create real liability.

Related US restrictions worth knowing: motor vehicle and driver records are

restricted to enumerated purposes under the Driver's Privacy Protection Act, and

some states restrict voter-file use to electoral purposes.

GDPR and the UK/EU position

The US-style people-search market barely exists in Europe, and what does exists on

much thinner data. Durable reasons: aggregating and publishing personal data needs

a lawful basis, and "we bought it" is not one; transparency obligations require

telling the data subject you hold their data, which is fatal to a scraped

aggregation business; special-category data is stricter again; and subjects have

access, rectification, erasure, and objection rights that are cheap to exercise

and expensive to service. Electoral registers, land registries, and court records

are correspondingly more restricted than their US equivalents.

If you are in scope of GDPR, your case file is processing too. You need a lawful

basis, a retention limit, and a defensible answer if the subject asks what you

hold. Legitimate interests is available but requires a documented balancing test.

Self-defense: audit and remove your own exposure

The most valuable use of this skill for most people. Run yourself through the

major brokers, record every profile URL, then work each opt-out. What to know:

  • Opt-outs are per-broker, deliberately tedious, and usually require finding your

own profile URL first. Some require email confirmation; some require identity

documents, which is its own risk.

  • Removals lapse. Brokers re-ingest from upstream, so a removed profile reappears

after a refresh cycle. It is recurring maintenance, not a one-time job.

  • Paid removal services automate the tedium across many brokers; they cannot reach

brokers with no opt-out, and they do not touch the public records underneath.

  • Jurisdiction helps. California created a broker registration requirement and a

statutory deletion mechanism intended to let a resident request deletion across

registered brokers at once; Vermont maintains a broker registry. Statutory

rights are more durable than per-site forms — use them.

  • The upstream source is the real fix: address confidentiality programmes for

at-risk people, opting out of the UK open electoral register, and holding

property through an entity are structural rather than cosmetic.

Searching yourself leaves a trace

Assume every search you run is logged, sold, and potentially visible.

  • Broker searches are logged against your account, IP, and payment identity, and

the search itself is data the broker can sell.

  • Some professional and social platforms notify a subject that you viewed their

profile, or surface you via contact-graph inference — uploading a contact list

is how investigators most often get made.

  • Some paid and investigator tiers notify the subject or generate a record

accessible to them; credit-header products can leave an inquiry trail.

  • Searching your own name from your own account creates the strongest possible

association between you and your identifiers.

Use investigate-without-getting-made before touching any of this on a sensitive

matter. Minimum: a separate browser profile, no account reuse, and never the

case's real contact details in a signup form.

Where this goes wrong

  • Confidence from repetition. Five brokers, one upstream vendor, one error.
  • Merged people presented as one. The profile looks coherent because the

merge is invisible; two address clusters in unconnected regions is the tell.

  • Deceased subjects. Records persist and sometimes merge with a same-name

living relative — a specific and damaging failure.

  • Recency illusion. "Last updated" reflects when the broker refreshed its

copy, not when the underlying fact was true.

  • Coverage collapses outside the US. Thin to nonexistent elsewhere; absence

of a result for a non-US subject means nothing at all.

  • Under-representation of the mobile and the young. People who rent, move

often, are recent immigrants, or have never held property or a landline are

systematically thin in these datasets. Sparse results are a sampling artefact.

  • Suppressed subjects. People who have opted out, or who are enrolled in an

address confidentiality programme, produce a clean result that is not evidence

of anything.

Confidence grading

  • Confirmed — the field is corroborated by a primary record (deed, court

filing, licence, registration) that names your subject and matches your anchor.

Cite the primary record; the broker drops out of the chain entirely.

  • Probable — corroborated by one independent non-broker source, with the

anchor matching and no conflicting record.

  • Unconfirmed — appears only on brokers, however many. Report as a lead with

the anchor basis stated.

  • Rejected — fails the anchor test, or conflicts with a primary record.

Keep it in the file assigned to a different candidate.

Never grade a claim higher because more brokers agree.

Worked example

Skip trace on a judgment debtor: name plus a last-known city.

  1. Two brokers return a profile with four addresses across two states, an age of

47, and six "relatives".

  1. Anchor test: the debtor's known employer city matches only two of the four

addresses. The other two go to a candidate B file.

  1. County recorder for the matching county shows a deed in the subject's name at

address 2, sold three years ago. Address 2 is confirmed as historical, not

current — the broker showed it as current.

  1. Dead end: a "relative" with a distinctive surname turns out, via the obituary

of the actual relative, to be a prior occupant of address 2. Dropped.

  1. Address 1 has no property record. The utility of the broker here was narrowing

four addresses to one with a real document behind it; everything else was noise.

  1. Confirmed selectors — one prior address, one middle initial from the deed —

go to the court file for the current service address.

Pivots

Selector producedFeed into
Candidate name from a reverse lookupfind-anyone
Email addresswhat-an-email-reveals
Phone numberwhose-number-is-this
Username or screen namehunt-a-handle
Employer or business namex-ray-a-company, who-really-owns-it
Address tied to a companywho-really-owns-it
Removed or changed broker profileread-deleted-pages
Relatives and associates clustergraph-the-network
Your own exposure inventorywhat-leaked-about-you

Legal and ToS notes

Scraping these sites breaches their terms and most deploy active anti-automation;

the business tiers exist precisely to sell you the API instead. Bulk collection of

personal data has its own exposure under computer-misuse and data-protection law

depending on where you and the data sit. Do not use non-FCRA data for FCRA-covered

decisions. Do not use broker data to locate a person who has taken steps to be

unlocatable unless you have a documented lawful basis — a court order, a

skip-trace mandate, an active investigation — and read [../../ETHICS.md](../../ETHICS.md)

before you start. This category is the raw material of doxxing and stalking, and

the same lookup is legitimate or criminal depending entirely on the objective you

wrote down at the start.

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skills/dig-through-data-brokers/SKILL.md