person-osint

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🇺🇸

Original

English

🇨🇳

Translation

Chinese

Person OSINT

个人开源情报（OSINT）

Profile a real individual from public, lawful sources. Input: a full name plus any anchor selector (city, employer, email, photo, handle).

从公开、合法的来源构建真实个人的档案。输入信息：全名以及任意锚定筛选条件（城市、雇主、邮箱、照片、账号昵称）。

Step 1 — Authorized scope

步骤1 — 授权范围

Read ../../ETHICS.md. Confirm this is not stalking, harassment, or doxxing. Note the legitimate objective (due diligence, fraud, missing person, hiring, self-audit). Done when written and lawful.

阅读../../ETHICS.md。确认本次操作不属于跟踪、骚扰或人肉搜索行为。明确合法目标（尽职调查、反欺诈、寻找失踪人员、招聘、自我审查）。完成标志：操作符合书面规范且合法。

Step 2 — Disambiguate

步骤2 — 身份去重

A name is a weak selector — many people share one. Anchor to something unique before pivoting: employer, city, school, birth year, a photo, a known handle. Done when you can tell your subject apart from namesakes, or you've flagged that you can't yet.

姓名是较弱的筛选条件——许多人同名。在展开挖掘前，先锚定某个唯一标识：雇主、城市、学校、出生年份、照片、已知账号昵称。完成标志：能够区分目标对象与同名人员，或已标注无法区分的情况。

Step 3 — Enumerate selectors

步骤3 — 枚举筛选条件

Collect, don't conclude. Pull public data into a selector list:

Search & dorks — name in quotes with each anchor; run
```
google-dorking
```
.
People search engines — see
```
people-search-engines
```
(pipl-style aggregators, voter/court records where lawful).
Social — find profiles across platforms; feed handles to
```
username-osint
```
.
Email / phone — if found, branch to
```
email-osint
```
/
```
phone-osint
```
.

Photos — run

reverse-image-search

and

exif-metadata-analysis

on any images;

geoint-photo

if location matters.

Professional — LinkedIn, company bios, conference talks, patents, papers, registries via
```
corporate-registries
```
.
Historical —
```
wayback-archives
```
for deleted bios and old profiles.

Done when every lead is captured as a selector with its source URL and date.

收集信息，而非急于下结论。将公开数据整理到筛选条件列表中：

搜索与谷歌语法 —— 将姓名加引号与每个锚定条件组合搜索；执行
```
google-dorking
```
。
人物搜索引擎 —— 参考
```
people-search-engines
```
（类似Pipl的聚合工具、合法获取的选民/法庭记录）。
社交平台 —— 查找各平台上的个人资料；将账号昵称导入
```
username-osint
```
工具。
邮箱/电话 —— 若找到相关信息，转向
```
email-osint
```
/
```
phone-osint
```
流程。
照片 —— 对所有图片执行
```
reverse-image-search
```
和
```
exif-metadata-analysis
```
；若地理位置重要，使用
```
geoint-photo
```
。
职业信息 —— LinkedIn、公司简介、会议演讲、专利、论文、通过
```
corporate-registries
```
获取的企业注册信息。
历史信息 —— 通过
```
wayback-archives
```
获取已删除的个人简介和旧资料。

完成标志：所有线索均被记录为筛选条件，并附带来源URL和日期。

Step 4 — Pivot and corroborate

步骤4 — 拓展验证

For each new selector, loop back to Step 3. Confirm identity only where two or more independent sources agree (e.g., same photo on a profile and a bio naming the same employer). Track confidence per claim: confirmed / probable / unverified. Reused usernames and profile photos are the strongest cross-platform links.

Done when pivots stop yielding new corroborated selectors.

针对每个新的筛选条件，返回步骤3循环操作。仅当两个或多个独立来源达成一致时（例如，同一照片出现在个人资料中，且简介提及同一雇主），才确认身份。记录每项信息的可信度：已确认/可能/未验证。重复使用的账号昵称和个人照片是跨平台关联的最强线索。

完成标志：拓展挖掘不再产生新的已验证筛选条件。

Step 5 — Report

步骤5 — 生成报告

Run

osint-report

. Separate confirmed facts from inferences, cite every claim, and drop anything that only serves to harm.

执行

osint-report

。将已确认事实与推断信息分开，为每项信息标注来源，剔除任何仅用于造成伤害的内容。