# vysecurity/LinkedInt

LinkedIn Recon Tool

Repository: https://github.com/vysecurity/LinkedInt
Canonical: https://ross.abutalabs.com/products/linkedint
Language: Python
License: MIT
License Family: permissive
Archived: true
Last push: 2023-03-06T13:05:38+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3100, "days_push": 1276, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1214, forks 212 (observed 2026-08-28T04:04:00.850569+00:00)

## What it is
LinkedInt is a Python CLI tool for LinkedIn reconnaissance that scrapes employee profiles for a target company and generates an HTML report with predicted email addresses. It uses LinkedIn credentials and optionally Hunter.io to determine email prefix formats.

## Use cases
- enumerate employees at a target company for pentest recon
- generate predicted corporate email addresses from LinkedIn profiles
- scrape LinkedIn search results into an offline HTML report
- gather OSINT on an organization during a red team engagement
- find email naming conventions using Hunter.io

## When to choose
- you need LinkedIn-based employee enumeration during authorized security assessments
- you want automated email prefix detection combined with profile scraping
- you prefer a lightweight Python CLI over browser-based OSINT tools

## When to avoid
- you need a maintained tool - LinkedIn frequently breaks scrapers and updates are sporadic
- you lack valid LinkedIn credentials or want to avoid account restrictions
- your use case is unauthorized scraping, which violates LinkedIn's terms

## Facets
- artifact type: cli-tool
- maturity: maintenance
- function: osint, web-scraping, security
- domain: osint, security, crawlers
- platform: python, cli, cross-platform
- tags: linkedin-recon, osint, email-enumeration, pentesting, reconnaissance

## Member repositories
- vysecurity/LinkedInt (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:00.850569+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:17:54.906076+00:00, confidence not recorded.
  - readme: https://github.com/vysecurity/LinkedInt (fetched 2026-08-28T04:04:00.850569+00:00, sha 47350bf1f9b6)
- Data as of 2026-08-30T08:39:29.467469+00:00.