LinkedInt

LinkedInt is an open-source Python tool available on GitHub that automates LinkedIn intelligence gathering using Google dorking techniques. Rather than scraping LinkedIn directly (which is aggressively blocked), LinkedInt uses Google's index of LinkedIn content to find profiles, extract employee information, and map corporate connections.

For OSINT investigators conducting corporate reconnaissance, LinkedIn is the premier source of professional identity and organizational structure data. LinkedInt automates the process of extracting this intelligence at scale using Google dork queries that search the LinkedIn data indexed by Google without triggering LinkedIn's own anti-scraping measures.

Employee enumeration for target organizations is the primary investigative application. LinkedInt can identify employees of a specific company by querying Google for LinkedIn profiles that list that company as their employer, returning names, job titles, and profile URLs for hundreds of employees. This employee list reveals organizational structure, department composition, and key personnel.

For spear-phishing simulations in authorized penetration testing, the employee list from LinkedInt provides targeting data — knowing the format of corporate email addresses (from Email Format tools) and having a complete employee list allows realistic phishing campaign targeting.

For corporate intelligence investigations, the employee roster reveals hiring patterns, specific expertise areas (visible from job titles and skills), executive leadership composition, and turnover patterns if compared with previous listings.

Job title analysis from LinkedIn data reveals the organizational hierarchy and functional divisions of a target company, providing intelligence about their operational structure that may not be otherwise disclosed.

LinkedInt's Google-based approach avoids LinkedIn's direct API restrictions but is subject to Google's rate limiting and LinkedIn's ongoing efforts to de-index certain content.

Document the target company, query date, number of profiles found, and relevant individual profiles identified for investigation records.