Sherlock Username Scraper — OSINT Account Search

What does Sherlock Username Scraper do?

Sherlock Username Scraper performs a Sherlock-style username-presence search. Search one or more usernames or handles across social media, forums and public sites such as github.com. Export profile URLs, confidence scores and per-username dossiers as JSON. Each confidence score describes the available account-presence evidence from 0 to 1. A shared username does not establish that accounts belong to the same person, and the score is not an identity probability. Each processed username also gets an unbilled dossier summarizing its results and checks that could not be verified. Its scanComplete field is false when a result cap, cost limit or error interrupted the scan; it is true when the selected checks finished, including any inconclusive checks.

For a first run, try topSites: 100 and maxResults: 10. maxResults limits profile rows across all usernames; dossiers are additional rows. With includeNotFound: true, completed negative checks are returned without a profile charge and count toward that row limit. A blocked check is inconclusive. Found matches below 0.5 are not billed; minConfidence filters the found matches you keep.

Every run is a fresh scan. Repeated matches can be billed again; there is no saved comparison history or incremental mode. To track your own handles over time, retain each dataset and compare username plus profileUrl in your workflow. The default selects the top 500 site entries. Unavailable or username-incompatible sites are skipped, and related sites can also be checked. The dossier reports the actual count. Use sites to focus on named platforms or increase topSites for broader coverage.

How to use this actor

• 👉 Register for a free Apify account — no credit card required.
• 🎉 Just click Sign up free on Apify → and complete a quick signup.
• 💰 A free Apify account includes $5 in monthly credits — enough to test this actor.
• ⏳ Scrape during the free trial, with no commitment or upfront payment required.

Key features

• 🎯 Every match scored, weak matches never billed: every found profile carries an evidence score from 0 to 1. It describes account-presence evidence observed during this run, not a probability that accounts belong to the same person. Scores can change when a site's response changes. Matches below 0.5 are never billed; use minConfidence to choose which found matches enter your dataset.
• 🗂️ Per-username exposure dossier: alongside the per-site matches, each processed username gets a dossier: an exposure score, the categories of sites where the handle appears, and any surfaced identity signals — a ready-made summary for investigators, analysts, and trust-and-safety teams.
• 🌐 Hundreds of sites in one run: check a username across a large catalog of sites in a single run, or narrow the search with sites, tags, excludeTags, and topSites to target only the platforms you care about.
• 🧹 Empty-field stripping: drop null, empty-string, and empty-array fields from each record before push. Smaller payloads for AI agents and dashboards that already handle missing fields gracefully.
• 📤 Export anywhere: Download the dataset as JSON, CSV, or Excel from the Apify Console, or stream live via the Apify API and integrations (Make, Zapier, Google Sheets, n8n, …).

What data can you extract from hundreds of sites?

Profile rows include the username, site name, profile URL, status, HTTP status and evidence score, with public details when available. Dossier rows summarize delivered findings and checked sites for each processed username; scanComplete identifies interrupted scans. The two record types have different fields. Unless excludeEmptyFields is enabled, unavailable profile details remain null.

Input

The main inputs are a result limit. Additional filters and options are available in the input schema.

Key parameters:

• maxResults — Maximum profile records to return across all usernames, including checked-but-not-found records when requested. 0 = unlimited. Unbilled per-username dossiers are additional rows. The search stops when this limit is reached. (default: 0)
• usernames — One or more usernames to search for across sites.
• topSites — Select this many top-ranked site entries per username. Unavailable or username-incompatible sites are skipped; related sites can also be checked. The dossier reports the actual number checked. Lower is faster and cheaper. (default: 500)
• sites — Restrict the search to specific site names (case-insensitive). Related sites can also be checked, such as GitHub Gist when selecting GitHub. Leave empty to use the broader site selection.
• tags — Only check sites tagged with these categories (e.g. coding, gaming, music).
• excludeTags — Skip sites tagged with these categories.
• minConfidence — Only return found matches at or above this evidence score (0–1). It measures confidence in account presence, not whether accounts belong to the same person. Leave at 0 to include weak matches; requested not-found checks are not filtered by this score. (default: 0)
• extractData — Pull profile details (display name, bio, location, avatar, linked accounts) from each match when available. (default: true)
• includeNotFound — Also return not-found profile records for completed checks. These records are never billed and do not count as found profiles. Blocked or inconclusive checks are not proof of absence. (default: false)
• excludeEmptyFields — Drop null, empty-string, and empty-array fields from each output record instead of including them. (default: false)
• notifyOnlyChanges — Compatibility option. This actor rescans on every run and has no incremental history, so all found profiles are treated as new and this option does not suppress repeated matches. (default: false)
• notificationLimit — Maximum number of listings included in each notification message (1–20). (default: 5)
• ...and 13 more parameters

Input examples

Try a bounded first search — Check a public example handle across the top 100 sites and stop after ten profile rows.

→ One profile record per site where the handle exists — each with a confidence score and profile URL — plus a single exposure dossier for the username.

{
  "usernames": [
    "torvalds"
  ],
  "topSites": 100,
  "maxResults": 10
}

High-confidence matches only — Check several handles but keep only strongly verified hits on the most popular sites.

→ Profile records scoring at or above your confidence threshold, limited to the top sites, with public profile details attached.

{
  "usernames": [
    "johnsmith",
    "j.smith"
  ],
  "topSites": 100,
  "minConfidence": 0.8,
  "extractData": true
}

Output

Each run produces a dataset of structured profile records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.

Example profile record

{
  "recordType": "profile",
  "username": "torvalds",
  "siteName": "GitHub",
  "profileUrl": "https://github.com/torvalds",
  "siteMainUrl": "https://www.github.com/",
  "status": "found",
  "httpStatus": 200,
  "rank": 10,
  "tags": [
    "coding"
  ],
  "confidence": 0.88,
  "verifiedBy": [
    "engine-a",
    "engine-b"
  ],
  "detectionMethod": "status_code",
  "fullName": "Linus Torvalds",
  "location": "Portland, OR",
  "image": "https://avatars.githubusercontent.com/u/1024025?v=4",
  "extractedIds": {
    "uid": "1024025",
    "image": "https://avatars.githubusercontent.com/u/1024025?v=4",
    "created_at": "2011-09-03T15:26:22Z",
    "location": "Portland, OR",
    "follower_count": "329726",
    "following_count": "0",
    "fullname": "Linus Torvalds",
    "public_gists_count": "1",
    "public_repos_count": "12",
    "company": "Linux Foundation"
  },
  "foundAt": "2026-10-28T22:13:04.392Z"
}

How to scrape hundreds of sites

1. Go to Sherlock Username Scraper in Apify Console.
2. Configure the input.
3. Set maxResults to control how many results you need.
4. Click Start and wait for the run to finish.
5. Export the dataset as JSON, CSV, or Excel.

Use cases

• Investigate a person of interest across social networks, forums, and niche communities from a single handle.
• Vet a username during fraud, trust-and-safety, or due-diligence checks and gauge its exposure at a glance.
• Map a subject's linked accounts and public identity signals for OSINT research and reporting.
• Monitor your own or a client's handle to see where it is present and reduce digital footprint.

How much does it cost to scrape hundreds of sites?

Sherlock Username Scraper uses pay-per-event pricing. You pay a small fee when the run starts and then for each result that is actually produced.

• Run start: $0.00005 per run
• Per result: $0.015 per profile record

Example costs:

• 10 results: $0.15
• 25 results: $0.38
• 100 results: $1.5
• 200 results: $3
• 500 results: $7.5

Platform usage is billed on top of these prices. The figures above are Apify event fees only. Compute units and proxy traffic are billed separately by Apify at your actual consumption, and for proxy- or browser-heavy workloads they can exceed the event fees. What you actually pay depends on your own input — how many results you request, the run memory you choose, and your proxy settings — so it cannot be stated as a fixed figure here. Every run reports its exact platform usage on the run detail page.

The Actor Start event is charged once per GB of run memory (minimum one), so a run configured with 2 GB is charged two start events rather than one.

FAQ

How many results can I get from hundreds of sites?

The number of results depends on the search query and available profiles on hundreds of sites. Use the maxResults parameter to control how many results are returned per run.

Can I integrate Sherlock Username Scraper with other apps?

Yes. Sherlock Username Scraper works with Apify's integrations to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

Can I use Sherlock Username Scraper with the Apify API?

Yes. You can start runs, manage inputs, and retrieve results programmatically through the Apify API. Client libraries are available for JavaScript, Python, and other languages.

Can I use Sherlock Username Scraper through an MCP Server?

Yes. Apify provides an MCP Server that lets AI assistants and agents call this actor directly. Use excludeEmptyFields to keep payloads manageable for LLM context windows.

Is it legal to scrape hundreds of sites?

This actor extracts publicly available data from hundreds of sites. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.

Your feedback

If you have questions, need a feature, or found a bug, please open an issue on the actor's page in Apify Console. Your feedback helps us improve.

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Getting started with Apify

New to Apify? Create a free account with $5 credit — no credit card required.

1. Sign up — $5 platform credit included
2. Open this actor and configure your input
3. Click Start — export results as JSON, CSV, or Excel

Need more later? See Apify pricing.

Plan a small first-run budget

Your maximum cost covers the start fee, billable profile matches and platform usage. A very low limit can end the run before any profile is delivered. For a smaller first search, choose fewer sites with topSites or sites, then set a budget that covers the selected search. Explicitly disabling proxies changes access reliability and can reduce coverage. A scheduled run with the same insufficient budget can repeat this empty outcome; each run is a fresh scan.

Disclaimer

Unofficial — not affiliated with the Sherlock project. "Sherlock" describes a similar username-presence search; this hosted actor does not promise identical site coverage or results to the Sherlock command-line tool.

Search keywords

github scraper, github api, apify github, github data extraction, sherlock username scraper, sherlock username api, apify sherlock username, sherlock username data extraction, github.com scraper, github.com data, github.com api, social media scraper, profile data.