LinkedIn Profile Scraper

Scrapes comprehensive data from public LinkedIn profiles: identity, work experience, education, skills, languages, certifications, and more. Optionally infers and verifies professional email addresses.

Built with Crawlee for Python + Camoufox (stealthy Firefox) for reliable scraping with minimal bot detection.

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Features

• Extracts full profile data: name, headline, summary, location, connections, followers, experience, education, skills, languages, certifications, publications, patents, volunteer work, recommendations
• Infers professional email addresses from company domain patterns
• Optional SMTP email verification
• Optional LinkedIn session cookie for authenticated scraping (unlocks more data)
• Optional Apify proxy or local Tor proxy support
• Pipeline mode: consume URLs from a named RequestQueue (for use with a discovery actor)
• Graceful per-profile error handling — one failure never aborts the whole run

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Input

Field	Type	Default	Description
profileUrls	string[]	—	LinkedIn /in/ profile URLs to scrape. Required (unless using inputRequestQueueName).
maxProfiles	integer	unlimited	Cap the number of profiles processed.
maxConcurrency	integer	1	Parallel browser tabs (max 5). Keep at 1–2 to avoid blocks.
requestDelay	integer	3000	Milliseconds to wait between requests. Higher = safer.
proxyConfiguration	object	disabled	Apify proxy config. Recommended when running on the platform.
linkedinCookies	string	—	Value of the li_at LinkedIn session cookie. Enables authenticated scraping.
verifyEmail	boolean	false	Verify inferred emails via SMTP. Slower but more accurate.
inputRequestQueueName	string	—	Name of an Apify RequestQueue to consume URLs from (pipeline mode). Overrides profileUrls.

Example input

{
  "profileUrls": [
    "https://www.linkedin.com/in/williamhgates",
    "https://www.linkedin.com/in/jeffweiner08"
  ],
  "maxConcurrency": 1,
  "requestDelay": 4000,
  "proxyConfiguration": { "useApifyProxy": true }
}

Using a session cookie

Providing a LinkedIn session cookie (li_at) allows the scraper to access authenticated profile data and greatly reduces the risk of bot blocks.

To find your cookie:

1. Log in to LinkedIn in your browser
2. Open DevTools → Application → Cookies → linkedin.com
3. Copy the value of li_at
4. Paste it into the linkedinCookies input field

The cookie is marked isSecret and will not appear in logs.

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Output

Each profile produces one record in the default dataset. On success:

{
  "linkedinUrl": "https://www.linkedin.com/in/williamhgates",
  "linkedinPublicUrl": "https://linkedin.com/in/williamhgates",
  "publicIdentifier": "williamhgates",
  "urn": "ACoAAABxN1IBk82L_jCY2opFKNZpSCCcsr6X1MU",
  "firstName": "Bill",
  "lastName": "Gates",
  "fullName": "Bill Gates",
  "headline": "Co-chair, Bill & Melinda Gates Foundation",
  "summary": "...",
  "profilePictureUrl": "https://...",
  "backgroundPictureUrl": "https://...",
  "location": "Seattle, Washington, United States",
  "connections": 500,
  "followers": 35000000,
  "email": "bill.gates@gatesfoundation.org",
  "emailVerificationStatus": "valid",
  "jobTitle": "Co-chair",
  "jobStartedOn": "2021-01",
  "jobLocation": "Seattle, Washington, United States",
  "jobStillWorking": true,
  "currentJobDuration": "4 yrs",
  "currentJobDurationInYrs": 4.0,
  "companyName": "Bill & Melinda Gates Foundation",
  "companyIndustry": "Non-profit Organizations",
  "companyWebsite": "https://www.gatesfoundation.org",
  "companyLinkedin": "https://www.linkedin.com/company/gatesfoundation",
  "companySize": "1001-5000",
  "experiences": [
    {
      "companyName": "Bill & Melinda Gates Foundation",
      "title": "Co-chair",
      "jobDescription": "...",
      "jobStartedOn": "2021-01",
      "jobEndedOn": null,
      "jobStillWorking": true,
      "jobLocation": "Seattle, Washington, United States",
      "companyWebsite": "https://www.gatesfoundation.org",
      "companyIndustry": "Non-profit Organizations",
      "companySize": "1001-5000"
    }
  ],
  "educations": [
    {
      "schoolName": "Harvard University",
      "degree": "...",
      "fieldOfStudy": "...",
      "startYear": 1973,
      "endYear": 1975
    }
  ],
  "skills": [{ "title": "Strategic Planning" }],
  "languages": [{ "name": "English", "proficiency": "NATIVE_OR_BILINGUAL" }],
  "certifications": [],
  "publications": [],
  "patents": [],
  "volunteerWork": [],
  "recommendations": [],
  "succeeded": true
}

On failure, a minimal error record is pushed and the run continues:

{
  "inputUrl": "https://www.linkedin.com/in/nonexistent-profile",
  "succeeded": false,
  "error": "Profile not found or access denied."
}

Email verification status values

Value	Meaning
valid	SMTP check passed — mailbox exists
invalid	SMTP check failed — address rejected
catch_all	Domain accepts all addresses — unverifiable
unverified	SMTP check skipped (verifyEmail is false)
no_email	No email was inferred

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Pipeline mode

This actor can consume profile URLs from a named Apify RequestQueue instead of the profileUrls input. This is useful when chaining it with a discovery actor that enqueues profiles for processing.

{
  "inputRequestQueueName": "linkedin-discovery-output"
}

Set inputRequestQueueName to the same value as the discovery actor's outputRequestQueueName. The scraper will drain the queue and process all URLs found.

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Anti-detection notes

• Keep maxConcurrency at 1 (default). LinkedIn blocks aggressive parallel scraping quickly.
• Increase requestDelay if you observe bot detection. 5000–10000 ms is safer for large batches.
• Use a proxy (proxyConfiguration) when running on the Apify platform — residential proxies work best.
• Provide a session cookie (linkedinCookies) to reduce blocks and access more profile data.
• The scraper uses Camoufox — a hardened Firefox with realistic browser fingerprints — which passes most bot-detection heuristics.

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Limitations

• Scrapes only publicly visible data. Fields hidden behind LinkedIn's login wall may not be available without a session cookie.
• LinkedIn's page structure changes frequently; some fields may occasionally fail to parse.
• Email inference is pattern-based (e.g. firstname.lastname@company.com) and not guaranteed to be correct. Use verifyEmail: true for higher accuracy.