inspy
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Python-based LinkedIn enumeration tool for discovering employees, domains, and email addresses by company name.
Summary
inspy is an open-source, python-based command-line tool for LinkedIn enumeration, letting a user supply a company name and pull employee lists by title or department, then automate domain and email discovery using the HunterIO API. It's built for red teamers and social-engineering assessors doing reconnaissance ahead of an engagement, generating output as HTML, CSV, JSON or XML for use in later phishing or profiling work. It sits in the OSINTOSINTOpen-source intelligence, collecting and analyzing information from publicly available sources. Investigators use it to learn about people, infrastructure or threats. recon space alongside other employee-enumeration tools, filling the specific niche of turning a company name into a working email-address list. The project has not aged well: first committed in 2016, it saw four contributors and six releases, but its own README now marks it deprecated and unmaintained, with no commits in the past year, so anyone shortlisting it should expect to fork and patch rather than rely on upstream support.
Python-based LinkedIn enumeration tool for discovering employees, domains, and email addresses by company name.
How inspy helps
Which employees at a target company can be found by their job title or department?
takes a company name plus a newline-delimited list of titles or departments and returns the matching employees found on LinkedIn
What is the email address format used by a target company?
pulls the company's domain and known address patterns from the HunterIO API so a discovered name can be turned into a working email
Which email addresses belong to the employees found at a target company?
combines the enumerated names with the discovered or supplied address format to generate a working email for each person
What does the harvested employee and email data look like for use in a phishing pretext or profiling writeup?
writes the results out as HTML, CSV, JSON or XML for handoff into later engagement work
Can a target's domain be found automatically instead of supplied by hand?
queries HunterIO with the company name to resolve the domain when one is not passed in directly
Languages
Command line
| option | found in | since | description |
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Values are placeholders taken from each option’s declared default. Nothing is executed here — the output shown is a recording of a run that already happened.
Score card
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Shipping velocity releases a month, last 12 months
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Documentation quality release-notes rubric, 0–100
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Breaking-change discipline how rarely a release breaks users, and notice given
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Maintenance risk quiet time against its own cadence, maintainers
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Innovation & surface new capabilities, API and MCP surface
- Community health
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Contributor trend distinct committers, this year against last
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Maintainer concentration bus factor now against a year ago
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Issue backlog trend issues closed per issue opened, 12 months
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Responsiveness median time to a maintainer’s first reply
Nine scores for inspy, each built from the releases, notes and API history this site tracks — and, on Researcher and Business, where it stands among every measured tool in its category and how that has moved.
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Blank means never measured; nothing here is a filled-in zero.
Peer standings are included with Researcher and Business. See how this tool ranks against its competitors, using data we don't publish anywhere else.
See plans →Each score is 0–100 on a published rubric, derived from data this site already shows. A dimension we cannot measure says so — it is never scored 0 and never enters a rank.
How this is scored
- Shipping velocity — releases a month over the last 12 months, on a log scale where 16 a month scores 100. Needs 3 releases in the window.
- Documentation quality — the release-notes rubric published on the analytics page, unchanged.
- Breaking-change discipline — the share of releases carrying a breaking change (none scores 100, half or more scores 0). Only projects that label breaking changes are measured: a clean record cannot be told from an unlabelled one.
- Maintenance risk — quiet time measured against the tool's own release cadence (quiet longer than 90 days and three typical gaps scores 0), plus the number of active maintainers and whether contributors are growing, where known. Higher is lower risk.
- Innovation & surface — new capabilities in the feature ledger this year, API and MCP operations added, and the share of commits that are features: the mean of whichever we hold.
- Community health (open-source tools only) — each is a direction, not a size: contributors this year against last, the bus factor now against a year ago, and issues closed per issue opened, where steady scores 50, doubled 100 and halved 0; plus the median time to a maintainer's first reply (an hour scores about 100, a month or more 0). A commercial card has no repository and carries none of the four.
- Documented delivery (commercial tools) — when a vendor's documented new capabilities have slowed against its own baseline, that counts against the overall standing as heavily as two low dimensions. Steady delivery, or too little history to judge, leaves the standing alone; it is never a sixth score.
- Open-source tools are scored on repository signals; commercial tools on their published changelog. Ranks compare tools within one category and one profile and need at least five measured peers; the overall standing needs three ranked dimensions. Best-in-breed or consolidator is a shape, not a quality, and is never scored.
Release-note detail over time
See how much detail inspy puts in its release notes, quarter by quarter, and compare it with tracked tools in the same category. This history uses up to ten retained, reviewed notes per tool; sparse or blank older quarters may reflect that limit.
Checking release-note history…
Releases
Nothing shipped since we started watching. Releases and docs updates land here as they happen.
Project health
Issue, contributor and maintainer activity in gojhonny/InSpy, 2023-10 – 2026-09, as of 2026-09-25. Twelve-month figures first; the trend lines run the whole window.
- Contributors 0 ±0 vs prior 12 months
- Maintainers 0 +0 joined · −0 left, last 12 months
- Bus factor 0 committers behind half the commits
- Community-filed not measured of issues opened, last 12 months
- Median time to close not measured issues closed, last 12 months
- Open backlog not measured open issues today
- Issues opened / month not measured
- Open backlog not measured
- Contributors / month 0
- Commits / month 0
- Stars 575
Counts from the project's public repository and git history; no individuals are identified. Maintainers are the committers covering 80% of the last year's commits. how we measure this
Libraries its release ships
What its latest release locks, checked against known advisories.None of its release's images build from a lockfile we can read.
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