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Mr Unknown alternatives & similar sites

Mr. Unknown | Schweizer Cybersecurity-Team für Unternehmen — 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
u-s-p.com ↗	72 match 1 shared topics	Umfassender Schweizer Cyber Security Service	de	information-and-network-security WordPress	robots llmsaihumans	email phone	none
admijalo.com ↗	71 match 1 shared topics	Admijalo – Cybersicherheit für Unternehmen	Germany~ de	information-and-network-security	robotsllmsaihumans	email phone	none
8com-holding.com ↗	71 match 1 shared topics	Cyber Security für Unternehmen & Behörden - 24/7 aus Deutschland	de	information-and-network-security	robotsllmsaihumans	emailphone	none
8com.io ↗	71 match 1 shared topics	Cyber Security für Unternehmen & Behörden - 24/7 aus Deutschland	de	information-and-network-security	robotsllmsaihumans	emailphone	none
cyber-security-deutschland.de ↗	69 match 1 shared topics	Cyber Security Deutschland \| IT-Sicherheit für Unternehmen – Betriebsfähig & Kontrolliert	Germany de	information-and-network-security	robotsllmsaihumans	emailphone	none
daseq.de ↗	68 match 1 shared topics	DASEQ GmbH - Cybersecurity, Consulting, Training	Germany de	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
tuvit-services.com ↗	68 match 1 shared topics	Informationssicherheit für Unternehmen \| TÜV TRUST IT	de	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
niemeier-group.com ↗	68 match 1 shared topics	ET-SEC E-Mail Sicherheit für ihr Unternehmen!	de	information-and-network-security Webflow	robotsllmsaihumans	emailphone	none
niemeier.com ↗	68 match 1 shared topics	ET-SEC E-Mail Sicherheit für ihr Unternehmen!	de	information-and-network-security Webflow	robotsllmsaihumans	emailphone	none
blisse.asia ↗	67 match 1 shared topics	Blisse \| Cybersecurity as a Service	de	information-and-network-security	robotsllmsaihumans	emailphone	none
blisse.berlin ↗	67 match 1 shared topics	Blisse \| Cybersecurity as a Service	de	information-and-network-security	robotsllmsaihumans	emailphone	none
blisse.net ↗	67 match 1 shared topics	Blisse \| Cybersecurity as a Service	de	information-and-network-security	robotsllmsaihumans	emailphone	none
deutor.de ↗	67 match 1 shared topics	Deutor – Cybersecurity	Germany de	information-and-network-security WordPress WooCommerce	robotsllmsaihumans	emailphone	none
cycademy.de ↗	67 match 1 shared topics	Cybersecurity für Executives & Krisensimulation \| Cycademy	Germany de	information-and-network-security	robotsllmsaihumans	emailphone	none
sopra-steria.at ↗	67 match 1 shared topics	Digitale Transformation & Cybersecurity \| Sopra Steria Österreich	Austria de	information-and-network-security	robotsllmsaihumans	emailphone	none
soprasteriagroup.at ↗	67 match 1 shared topics	Digitale Transformation & Cybersecurity \| Sopra Steria Österreich	Austria de	information-and-network-security	robotsllmsaihumans	emailphone	none
soprasteria.at ↗	67 match 1 shared topics	Digitale Transformation & Cybersecurity \| Sopra Steria Österreich	Austria de	information-and-network-security	robotsllmsaihumans	emailphone	none
soprasteria-group.at ↗	67 match 1 shared topics	Digitale Transformation & Cybersecurity \| Sopra Steria Österreich	Austria de	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.