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Keyonline24 alternatives & similar sites

Antivirus and Cybersecurity software buy cheap online at Keyonline24 — 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 Software And Applications →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
crypttrap.com ↗	72 match 2 shared topics	CRYPTTRAP — Cybersecurity Software	de	information-and-network-security	robotsllmsaihumans	emailphone	none
sq-software.com ↗	70 match 2 shared topics	SQ-Software GmbH - Cyber Security Lösungen	de	information-and-network-security Weebly	robotsllmsaihumans	emailphone	none
cloud-metrics.de ↗	68 match 2 shared topics	MHM \| Software Supply Chain Security & Audit-Trail	Germany de	information-and-network-security	robotsllmsaihumans	emailphone	none
appnoe.de ↗	67 match 2 shared topics	Appnö - Software · Security	Germany de	software-and-applications	robotsllmsaihumans	emailphone	none
eset.ch ↗	66 match 2 shared topics	ESET Antivirus \| Virenschutz für Privat und Unternehmen \| ESET	Switzerland de	information-and-network-security TYPO3	robotsllmsaihumans	emailphone	none
chcrypt.ch ↗	66 match 2 shared topics	Sicherheitssoftware SecureCenter	Switzerland de	information-and-network-security	robotsllmsaihumans	email phone	none
codelotsen.de ↗	66 match 2 shared topics	CyberRisikoCheck, IT-Sicherheit & Software für KMU in Norddeutschland \| codeLotsen GmbH	Germany de	software-and-applications	robots llmsaihumans	email phone	none
codelotse.de ↗	66 match 2 shared topics	CyberRisikoCheck, IT-Sicherheit & Software für KMU in Norddeutschland \| codeLotsen GmbH	Germany de	software-and-applications	robots llmsaihumans	email phone	none
applicationsecuritycenter.com ↗	65 match 2 shared topics	APPVISORY – Mobile Security & App Risk Management	de	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
appsecuritycenter.com ↗	65 match 2 shared topics	APPVISORY – Mobile Security & App Risk Management	de	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
appvisory.com ↗	65 match 2 shared topics	APPVISORY – Mobile Security & App Risk Management	de	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
appvisory.net ↗	65 match 2 shared topics	APPVISORY – Mobile Security & App Risk Management	de	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
appsecuritycenter.de ↗	65 match 2 shared topics	APPVISORY – Mobile Security & App Risk Management	Germany de	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
apptesting.de ↗	65 match 2 shared topics	APPVISORY – Mobile Security & App Risk Management	Germany de	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
bundesappstore.de ↗	65 match 2 shared topics	APPVISORY – Mobile Security & App Risk Management	Germany de	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
daccord.de ↗	64 match 2 shared topics	IAM Software daccord - Zugriffsrechte sicher verwalten: daccord	Germany de	software-and-applications TYPO3	robotsllmsaihumans	emailphone	none
datalab.de ↗	64 match 2 shared topics	Datalab Software GmbH	Germany de	software-and-applications	robotsllmsaihumans	emailphone	none
h-solution.ch ↗	64 match 2 shared topics	Automation, Software & IT-Lösungen - Huber Solution GmbH	Switzerland de	software-and-applications WordPress	robots llmsaihumans	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.