# Maigret Username OSINT | $7/1K | Dossier + Deep Intel (`apivault_labs/maigret-username-osint`) Actor Search a username across 3000+ sites (Maigret, MIT) and get more than a hit list: an identity dossier, exposure score (0-100), category breakdown, names/locations/emails and risk flags. Standard $7/1K; Deep tier ($15/1K) adds account timeline, phones, sites and follower reach. - **URL**: https://apify.com/apivault\_labs/maigret-username-osint.md - **Developed by:** [Apivault Labs](https://apify.com/apivault_labs) (community) - **Categories:** Developer tools, Business, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $7.00 / 1,000 profile founds 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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## Maigret Username OSINT — 3000+ Sites, Identity Dossier & Exposure Score Search any username across **3000+ websites** and get more than a raw hit list. This Actor runs the open-source [Maigret](https://github.com/soxoj/maigret) engine and adds an **intelligence layer** on top: a consolidated identity dossier, an explainable exposure score, category and country breakdowns, discovered identities, and risk flags. Built for security researchers, journalists, threat intelligence teams, and authorized investigations. > **Search only usernames you are authorized to investigate.** This Actor checks > publicly accessible pages — the same pages anyone can open in a browser. It > does not bypass authentication or access private data. ### Why this beats a plain Maigret wrapper Most username-search actors give you one row per hit and stop there. This one turns hundreds of scattered hits into an answer: - **Identity dossier** — one consolidated record per username with every found profile, plus discovered real names, locations, emails, bios, avatars, and linked accounts pulled from profile pages. - **Exposure score (0-100) + tier** — an explainable "how findable is this identity" rating, with the exact reasons that produced the number. - **Category & country breakdown** — see where the footprint actually lives (social, coding, gaming, finance, adult, country-specific sites). - **Risk flags** — `realNameExposed`, `locationExposed`, `emailExposed`, `sensitivePresence`, `highValueTargets`, `linkedAccountsFound`. - **Recursive search (optional)** — pivots on discovered identifiers to widen the dossier in a second pass. - **Bulk usernames** — investigate several handles in one run. - **Pay only for hits, two tiers** — billed per **found profile**, never for a username that turns up nothing, and never for the dossier or summary: - **Standard — $7/1K** ($0.007/profile): presence + name/bio/location/avatar, dossier, exposure score, risk flags. ~30% cheaper than comparable actors. - **Deep — $15/1K** ($0.015/profile, set `deepEnrichment: true`): everything above **plus** account-creation timeline (digital-footprint age), phone numbers, personal websites/domains, and cross-platform follower reach. ### Input | Field | Type | Description | Default | |-------|------|-------------|---------| | `usernames` | array | Usernames to investigate (one dossier each) | required | | `topSites` | integer | Sites to check by popularity; `0` = all 3000+ | `500` | | `tags` | array | Include only these site categories/countries | — | | `excludeTags` | array | Skip sites with these tags (e.g. `nsfw`) | — | | `sites` | array | Check only these exact site names | — | | `extractData` | boolean | Parse profile pages for names/bio/IDs | `true` | | `deepEnrichment` | boolean | **Deep tier ($15/1K)** — adds timeline, phones, websites, follower reach | `false` | | `recursiveSearch` | boolean | Pivot on discovered identifiers | `false` | | `includeNotFound` | boolean | Also emit "not found" rows | `false` | | `perSiteRecords` | boolean | Emit one record per found profile | `true` | | `exportFormat` | string | `default` JSON or flat `csv` | `default` | | `timeout` | integer | Per-request timeout (seconds) | `30` | | `maxConnections` | integer | Parallel connections | `50` | | `proxyUrl` | string | Optional HTTP/SOCKS proxy | — | #### Example input ```json { "usernames": ["johndoe"], "topSites": 500, "extractData": true, "recursiveSearch": false, "exportFormat": "default" } ```` ### Output #### Dossier record (one per username) ```json { "recordType": "dossier", "username": "johndoe", "sitesChecked": 500, "profilesFound": 23, "exposureScore": 68, "exposureTier": "high", "exposureReasons": [ "23 profiles found (+30)", "4 distinct categories (+12)", "real name exposed (+12)", "email exposed (+12)" ], "categoryBreakdown": {"social": 9, "coding": 5, "gaming": 4, "other": 5}, "countries": ["us"], "discoveredNames": ["John Doe"], "discoveredLocations": ["San Francisco, CA"], "discoveredEmails": ["john@example.com"], "linkedIdentifiers": ["johndoe92", "j.doe"], "riskFlags": { "realNameExposed": true, "locationExposed": true, "emailExposed": true, "sensitivePresence": false, "highValueTargets": false, "linkedAccountsFound": true }, "foundProfiles": [ {"siteName": "GitHub", "profileUrl": "https://github.com/johndoe", "tags": ["coding"]} ] } ``` #### Found-profile record (one per hit, when `perSiteRecords` is on) Every found profile carries the headline fields flat at the top level (a drop-in superset of a classic Maigret-style row), plus the full `extractedIds` map for power users: ```json { "recordType": "profile", "username": "johndoe", "siteName": "GitHub", "profileUrl": "https://github.com/johndoe", "siteMainUrl": "https://github.com", "status": "Claimed", "httpStatus": 200, "isSimilar": false, "rank": 65, "alexaRank": 65, "tags": ["coding"], "fullName": "John Doe", "bio": "Software Engineer", "location": "San Francisco, CA", "image": "https://avatars.githubusercontent.com/johndoe", "extractedIds": {"github_id": "12345", "fullname": "John Doe"}, "scrapedAt": "2026-06-01T00:00:00.000Z" } ``` A free **SUMMARY** record is written to the run's key-value store with per-username exposure scores and top categories. #### Deep tier (`deepEnrichment: true`, $15/1K) In the deep tier each found profile also carries `accountCreated`, `accountAgeYears`, `website`, `phone`, and `followers` where available, and the dossier gains a `deepIntel` block: ```json { "recordType": "dossier", "tier": "deep", "username": "johndoe", "deepIntel": { "phones": ["+1 415 555 0142"], "personalWebsites": ["https://johndoe.com"], "timeline": { "earliestAccount": {"site": "Twitch", "date": "2014-08-30", "year": 2014}, "earliestYear": 2014, "digitalFootprintAgeYears": 12, "accountsByYear": [{"site": "Twitch", "year": 2014}, {"site": "Imgur", "year": 2017}] }, "totalFollowersAcrossPlatforms": 18400, "reachByPlatform": [{"site": "YouTube", "followers": 17000}] } } ``` ### Tips - **Fast sweep:** set `topSites` to 100–200 for a quick major-platform check. - **Deep dossier:** set `topSites` to `0` to scan all 3000+ sites. - **Focus:** use `tags: ["social"]` or `tags: ["coding"]` to narrow the scan. - **Monitoring:** schedule a weekly run to detect new account registrations. ### Legal & disclaimer This Actor is an unofficial integration of [Maigret](https://github.com/soxoj/maigret) (MIT License). It is **not** affiliated with, endorsed by, or sponsored by the Maigret project or its authors. Provided for legitimate security research, journalism, and authorized investigations only. You are solely responsible for complying with applicable laws (GDPR, CCPA, local regulations) and the Terms of Service of checked sites. Do not use results to harass, stalk, or harm anyone. # Actor input Schema ## `usernames` (type: `array`): One or more usernames to investigate (e.g. 'johndoe'). Each username gets its own dossier record. Keep batches small — every checked username runs hundreds of HTTP requests. ## `topSites` (type: `integer`): How many sites to scan, ranked by popularity. 100-300 = fast major-platform sweep, 500 = balanced (default), 0 = all 3000+ sites (slowest, most thorough). ## `tags` (type: `array`): Restrict the scan to site categories/countries (e.g. social, coding, photo, gaming, us, ru). Empty = no tag restriction. ## `excludeTags` (type: `array`): Skip sites with these tags (e.g. nsfw, dating). Applied after the include filter. ## `sites` (type: `array`): Check only these exact site names (e.g. GitHub, Reddit, Instagram). Overrides the site-count / tag filters when set. ## `extractData` (type: `boolean`): Parse found profile pages with socid\_extractor to pull full names, bios, locations, emails, avatars, and linked-account IDs. Powers the dossier. Slightly slower. ## `deepEnrichment` (type: `boolean`): Unlock the DEEP tier: in addition to the standard fields, extract account creation timeline (digital-footprint age), phone numbers, personal websites/domains, and cross-platform follower reach, plus a deepIntel block in the dossier. Found profiles are billed at the premium rate ($0.015 each) instead of the standard rate ($0.007). Off = standard tier. ## `recursiveSearch` (type: `boolean`): When profile parsing reveals other usernames/IDs, run a second sweep on the most promising one to widen the dossier. Adds one extra search pass. Off by default to keep runs cheap. ## `includeNotFound` (type: `boolean`): Also push per-site records for sites where the username was NOT found. Off by default (you are not charged for these, and they bloat the dataset). ## `perSiteRecords` (type: `boolean`): In addition to the dossier, push one dataset record per found profile (the classic Maigret-style output). The dossier is always written regardless. ## `exportFormat` (type: `string`): default = rich JSON. csv = flat one-row-per-found-profile CSV ready for spreadsheets / case management. ## `timeout` (type: `integer`): How long to wait for each individual site before giving up. ## `maxConnections` (type: `integer`): How many sites to check in parallel. Higher = faster but heavier. 50 is a safe default. ## `maxProfilesPerUsername` (type: `integer`): Hard cap on how many found profiles are pushed AND billed per username. Default 0 = no limit (return every match). Set a positive number (e.g. 150) as a cost guard against runaway charges on very common usernames; extra hits beyond the cap are dropped, keeping the highest-ranked sites. ## `runBudgetSecs` (type: `integer`): Safety budget for the entire run. If reached, the Actor stops before starting the next username so it never burns compute indefinitely. Default 900 (15 min). ## `proxyUrl` (type: `string`): Route checks through an HTTP/SOCKS proxy (e.g. socks5://user:pass@host:port). Useful for WAF-protected sites that block datacenter IPs. Leave empty to go direct. ## Actor input object example ```json { "usernames": [ "soxoj" ], "topSites": 500, "tags": [], "excludeTags": [], "sites": [], "extractData": true, "deepEnrichment": false, "recursiveSearch": false, "includeNotFound": false, "perSiteRecords": true, "exportFormat": "default", "timeout": 30, "maxConnections": 50, "maxProfilesPerUsername": 0, "runBudgetSecs": 900 } ``` # 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 = { "usernames": [ "soxoj" ], "tags": [], "excludeTags": [], "sites": [] }; // Run the Actor and wait for it to finish const run = await client.actor("apivault_labs/maigret-username-osint").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 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); }); // 📚 Want to learn more 📖? Go to → 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 = { "usernames": ["soxoj"], "tags": [], "excludeTags": [], "sites": [], } # Run the Actor and wait for it to finish run = client.actor("apivault_labs/maigret-username-osint").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "usernames": [ "soxoj" ], "tags": [], "excludeTags": [], "sites": [] }' | apify call apivault_labs/maigret-username-osint --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=apivault_labs/maigret-username-osint", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Maigret Username OSINT | $7/1K | Dossier + Deep Intel", "description": "Search a username across 3000+ sites (Maigret, MIT) and get more than a hit list: an identity dossier, exposure score (0-100), category breakdown, names/locations/emails and risk flags. Standard $7/1K; Deep tier ($15/1K) adds account timeline, phones, sites and follower reach.", "version": "1.0", "x-build-id": "03LqAg0gx7Uuqb5pR" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/apivault_labs~maigret-username-osint/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-apivault_labs-maigret-username-osint", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/apivault_labs~maigret-username-osint/runs": { "post": { "operationId": "runs-sync-apivault_labs-maigret-username-osint", "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/apivault_labs~maigret-username-osint/run-sync": { "post": { "operationId": "run-sync-apivault_labs-maigret-username-osint", "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", "required": [ "usernames" ], "properties": { "usernames": { "title": "Usernames", "type": "array", "description": "One or more usernames to investigate (e.g. 'johndoe'). Each username gets its own dossier record. Keep batches small — every checked username runs hundreds of HTTP requests.", "items": { "type": "string" } }, "topSites": { "title": "Number of sites to check", "minimum": 0, "maximum": 3000, "type": "integer", "description": "How many sites to scan, ranked by popularity. 100-300 = fast major-platform sweep, 500 = balanced (default), 0 = all 3000+ sites (slowest, most thorough).", "default": 500 }, "tags": { "title": "Include only these tags", "type": "array", "description": "Restrict the scan to site categories/countries (e.g. social, coding, photo, gaming, us, ru). Empty = no tag restriction.", "items": { "type": "string" } }, "excludeTags": { "title": "Exclude these tags", "type": "array", "description": "Skip sites with these tags (e.g. nsfw, dating). Applied after the include filter.", "items": { "type": "string" } }, "sites": { "title": "Specific site names only", "type": "array", "description": "Check only these exact site names (e.g. GitHub, Reddit, Instagram). Overrides the site-count / tag filters when set.", "items": { "type": "string" } }, "extractData": { "title": "Extract profile data (names, bio, IDs)", "type": "boolean", "description": "Parse found profile pages with socid_extractor to pull full names, bios, locations, emails, avatars, and linked-account IDs. Powers the dossier. Slightly slower.", "default": true }, "deepEnrichment": { "title": "Deep enrichment (premium tier — $15/1K)", "type": "boolean", "description": "Unlock the DEEP tier: in addition to the standard fields, extract account creation timeline (digital-footprint age), phone numbers, personal websites/domains, and cross-platform follower reach, plus a deepIntel block in the dossier. Found profiles are billed at the premium rate ($0.015 each) instead of the standard rate ($0.007). Off = standard tier.", "default": false }, "recursiveSearch": { "title": "Recursive search on discovered identifiers", "type": "boolean", "description": "When profile parsing reveals other usernames/IDs, run a second sweep on the most promising one to widen the dossier. Adds one extra search pass. Off by default to keep runs cheap.", "default": false }, "includeNotFound": { "title": "Include 'not found' sites in dataset", "type": "boolean", "description": "Also push per-site records for sites where the username was NOT found. Off by default (you are not charged for these, and they bloat the dataset).", "default": false }, "perSiteRecords": { "title": "Also emit one record per found profile", "type": "boolean", "description": "In addition to the dossier, push one dataset record per found profile (the classic Maigret-style output). The dossier is always written regardless.", "default": true }, "exportFormat": { "title": "Export format", "enum": [ "default", "csv" ], "type": "string", "description": "default = rich JSON. csv = flat one-row-per-found-profile CSV ready for spreadsheets / case management.", "default": "default" }, "timeout": { "title": "Per-request timeout (seconds)", "minimum": 5, "maximum": 120, "type": "integer", "description": "How long to wait for each individual site before giving up.", "default": 30 }, "maxConnections": { "title": "Max parallel connections", "minimum": 1, "maximum": 100, "type": "integer", "description": "How many sites to check in parallel. Higher = faster but heavier. 50 is a safe default.", "default": 50 }, "maxProfilesPerUsername": { "title": "Max billed profiles per username (0 = no limit)", "minimum": 0, "maximum": 3000, "type": "integer", "description": "Hard cap on how many found profiles are pushed AND billed per username. Default 0 = no limit (return every match). Set a positive number (e.g. 150) as a cost guard against runaway charges on very common usernames; extra hits beyond the cap are dropped, keeping the highest-ranked sites.", "default": 0 }, "runBudgetSecs": { "title": "Whole-run time budget (seconds)", "minimum": 60, "maximum": 3600, "type": "integer", "description": "Safety budget for the entire run. If reached, the Actor stops before starting the next username so it never burns compute indefinitely. Default 900 (15 min).", "default": 900 }, "proxyUrl": { "title": "Custom proxy URL (optional)", "type": "string", "description": "Route checks through an HTTP/SOCKS proxy (e.g. socks5://user:pass@host:port). Useful for WAF-protected sites that block datacenter IPs. Leave empty to go direct." } } }, "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 } } } } } } } } } } ```