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Phishing - Wikipedia — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Information And Network Security →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
acumenis.training ↗	67 match 1 shared topics	Oops! That was Phishing!	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0penai-gpt.com ↗	66 match 1 shared topics	Phishing Simulation Landing Page	en	information-and-network-security	robotsllmsaihumans	emailphone	none
2fanotifications.com ↗	66 match 1 shared topics	Phishing Simulation Landing Page	en	information-and-network-security	robotsllmsaihumans	emailphone	none
1f.io ↗	66 match 1 shared topics	Phishing Simulation & Awareness Training - Fished	en	information-and-network-security	robotsllmsaihumans	emailphone	none
clickimmunity.com ↗	66 match 1 shared topics	Click Immune \| Modern Phishing Defense	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
spoofy.cloud ↗	65 match 1 shared topics	Spoofy.Cloud - Phishing as a Service for B2B	en	information-and-network-security	robotsllmsaihumans	emailphone	none
elitereefsecure.com ↗	64 match 1 shared topics	ReefSecure Angler - Professional Phishing Awareness Training	Belgium~ en	information-and-network-security	robotsllmsaihumans	email phone	none
onlrine-hmrc.co.uk ↗	64 match 1 shared topics	Avoid and report internet scams and phishing: Report internet scams and phishing - GOV.UK	United Kingdom en	information-and-network-security	robotsllmsaihumans	emailphone	none
onllne-hmrc-gov.uk ↗	64 match 1 shared topics	Avoid and report internet scams and phishing: Report internet scams and phishing - GOV.UK	United Kingdom en	information-and-network-security	robotsllmsaihumans	emailphone	none
online-hmric-gov.uk ↗	64 match 1 shared topics	Avoid and report internet scams and phishing: Report internet scams and phishing - GOV.UK	United Kingdom en	information-and-network-security	robotsllmsaihumans	emailphone	none
online-hmric-gov.co.uk ↗	64 match 1 shared topics	Avoid and report internet scams and phishing: Report internet scams and phishing - GOV.UK	United Kingdom en	information-and-network-security	robotsllmsaihumans	emailphone	none
onliine-hmrc.uk ↗	64 match 1 shared topics	Avoid and report internet scams and phishing: Report internet scams and phishing - GOV.UK	United Kingdom en	information-and-network-security	robotsllmsaihumans	emailphone	none
onliens-hmrc.co.uk ↗	64 match 1 shared topics	Avoid and report internet scams and phishing: Report internet scams and phishing - GOV.UK	United Kingdom en	information-and-network-security	robotsllmsaihumans	emailphone	none
alluresecurity.com ↗	64 match 1 shared topics	Brand Protection & Phishing Takedown Services - Allure Security	en	information-and-network-security WordPress WooCommerce	robots llmsaihumans	emailphone	none
vocaguard.com ↗	64 match 1 shared topics	VocaGuard - Your shield against phone scams, phishing and fraud	en	information-and-network-security	robotsllmsaihumans	emailphone	none
nobileconsulting.com ↗	64 match 1 shared topics	Nobile Consulting - Home	Italy~ en	information-and-network-security Joomla	robotsllmsaihumans	emailphone	partial · 8
capsplatform.com ↗	64 match 1 shared topics	CAPS - Advanced Phishing Simulation & Security Awareness Training	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
cryptophoto.com ↗	64 match 1 shared topics	Block phishing and malware using CryptoPhoto - vmcpsj.cryptophoto.com	en	information-and-network-security	robotsllmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.