# ๐Ÿ” OSINT People Search - 10+ Platforms Digital Footprint Lookup (`unrivaled_fortress/osint-person-lookup`) Actor Find digital footprints across 10+ platforms: GitHub, Reddit, GitLab, Keybase, Medium, Dev.to, Twitch, Instagram and more. People search for investigators and recruiters. Try free. - **URL**: https://apify.com/unrivaled\_fortress/osint-person-lookup.md - **Developed by:** [David Ahn](https://apify.com/unrivaled_fortress) (community) - **Categories:** Other, Lead generation - **Stats:** 9 total users, 6 monthly users, 96.7% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## ๐Ÿ” OSINT People Search - Digital Footprint & Social Profiles **Find digital footprints across the internet** from a name, username, or email. Searches **10+ platforms** for social profiles, code repositories and online mentions โ€” **no API key required**. ### โœจ Features - ๐Ÿ”Ž **10 platforms**: GitHub, Reddit, GitLab, npm, Keybase, Medium, Dev.to, Twitch, Instagram, Mastodon - ๐Ÿ‘ค **Name + username + email** as input - ๐Ÿ“Š Returns profile URL, avatar, bio, and metadata per match - ๐Ÿ”„ **Batch mode**: search multiple queries in one run - ๐ŸŽฏ **Source selection**: search all or pick specific platforms - ๐Ÿšซ **No API key** โ€” uses public endpoints, no tokens required - ๐Ÿ“ˆ Export as JSON / CSV / Excel ### ๐Ÿ“ฅ Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `query` | string | โ€” | Person name, username, or email to search | | `queries` | array | [] | Multiple queries for batch search | | `sources` | array | ["all"] | Sources: github, reddit, gitlab, npm, keybase, medium, devto, twitch, instagram, mastodon | | `maxResults` | integer | 20 | Max total results across all queries | ### ๐Ÿ“ค Output Each item: `source`, `type`, `username`, `name`, `url`, `avatar`, `bio`, `metadata`, `query`. ### ๐Ÿ’ก Use Cases - **Background checks**: aggregate public social profiles - **Recruiters**: find developer profiles (GitHub, GitLab, npm, Dev.to) - **Brand monitoring**: locate mentions on social platforms - **Investigations**: trace digital footprints for research ### ๐Ÿ’ฐ Pricing **from $1.50 / 1,000 results** โ€” pay only for data returned. ### โญ Reviews This Actor helped you? A quick rating helps others find it too โ€” please leave a review. ### ๐Ÿ“Œ Changelog - **v1.0** โ€” Public release (GitHub, Reddit, GitLab, npm) - **v1.1** โ€” Added Keybase, Medium, Dev.to, Twitch, Instagram (6โ†’10 sources) - **v1.2** โ€” Batch queries and source selection support ### ๐Ÿ”ง Support Issues or feature requests? Open an issue directly on this Actor's *Issues* tab โ€” average response time: under 24h. --- **Crafted by [David Ahn](https://apify.com/unrivaled_fortress)** ยท Built with [Apify](https://apify.com) + [Crawlee](https://crawlee.dev) (open-source) # Actor input Schema ## `query` (type: `string`): Person name, username, or email to search. ## `queries` (type: `array`): Multiple queries to search in one run. ## `sources` (type: `array`): Sources to search. Use ['all'] for everything. ## `maxResults` (type: `integer`): Max total results across all queries. ## Actor input object example ```json { "queries": [], "sources": [ "all" ], "maxResults": 20 } ```` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "queries": [], "sources": [ "all" ] }; // Run the Actor and wait for it to finish const run = await client.actor("unrivaled_fortress/osint-person-lookup").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "queries": [], "sources": ["all"], } # Run the Actor and wait for it to finish run = client.actor("unrivaled_fortress/osint-person-lookup").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "queries": [], "sources": [ "all" ] }' | apify call unrivaled_fortress/osint-person-lookup --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=unrivaled_fortress/osint-person-lookup", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "๐Ÿ” OSINT People Search - 10+ Platforms Digital Footprint Lookup", "description": "Find digital footprints across 10+ platforms: GitHub, Reddit, GitLab, Keybase, Medium, Dev.to, Twitch, Instagram and more. People search for investigators and recruiters. Try free.", "version": "1.0", "x-build-id": "lXB59kDkrOQORjL83" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/unrivaled_fortress~osint-person-lookup/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-unrivaled_fortress-osint-person-lookup", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/unrivaled_fortress~osint-person-lookup/runs": { "post": { "operationId": "runs-sync-unrivaled_fortress-osint-person-lookup", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/unrivaled_fortress~osint-person-lookup/run-sync": { "post": { "operationId": "run-sync-unrivaled_fortress-osint-person-lookup", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "query": { "title": "Single Query", "type": "string", "description": "Person name, username, or email to search." }, "queries": { "title": "Batch Queries", "type": "array", "description": "Multiple queries to search in one run.", "items": { "type": "string" } }, "sources": { "title": "Sources", "type": "array", "description": "Sources to search. Use ['all'] for everything.", "items": { "type": "string", "enum": [ "all", "github", "reddit", "gitlab", "npm", "mastodon", "keybase", "medium", "devto", "twitch", "instagram" ] } }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 500, "type": "integer", "description": "Max total results across all queries.", "default": 20 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```