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urlScore.ai - AI URL Scanner to Detect Phishing, Malware & Scam Websites — 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
6scan.com ↗	69 match 1 shared topics	6Scan - Website Malware Scanning, Clean-Up	en	information-and-network-security Webflow	robotsllmsaihumans	emailphone	none
luminir.io ↗	69 match 1 shared topics	Luminir - AI-Powered Phishing Detection	en	information-and-network-security	robotsllmsaihumans	emailphone	none
sanesecurity.co.uk ↗	68 match 1 shared topics	Sanesecurity ClamAV Malware, Phishing, and Spam Signatures	GB en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
azgadsecurity.com ↗	67 match 1 shared topics	Home \| AZGAD WEBSITE Security, Malware Cleanup Service	en	information-and-network-security	robotsllmsaihumans	emailphone	none
abusemanager.com ↗	67 match 1 shared topics	Domain Abuse Monitoring Software - Real-time Threat Detection \| iQ Global	en	information-and-network-security	robotsllmsaihumans	emailphone	none
pixelguard.app ↗	67 match 1 shared topics	PixelGuard - Detect pixelated images across your website	en	information-and-network-security	robotsllmsaihumans	emailphone	none
cavarette.com ↗	66 match 1 shared topics	Free Website Security Scanner - Discover Vulnerabilities \| Cavarette	en	information-and-network-security	robotsllmsaihumans	emailphone	none
lukeacha.com ↗	66 match 1 shared topics	LukeAcha.com \| Malware Analysis and Detection Research	en	information-and-network-security	robotsllmsaihumans	emailphone	none
bannerscanner.com ↗	66 match 1 shared topics	Banner Scanner — Website Privacy Compliance	en	information-and-network-security	robotsllmsaihumans	emailphone	none
lucaslinkowski.com ↗	66 match 1 shared topics	Lucas Linkowski \| Malware Defense, Reverse Engineering, Detection Engineering	GB~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
dimva.org ↗	66 match 1 shared topics	DIMVA - Conference on Detection of Intrusions and Malware & Vulnerability Assessment	en	information-and-network-security	robotsllmsaihumans	emailphone	none
abyssguard.com ↗	66 match 1 shared topics	AbyssGuard \| Website Protection API & Threat Detection	en	information-and-network-security PrestaShop	robotsllmsaihumans	emailphone	none
usebouncer.dev ↗	65 match 1 shared topics	Bouncer - Malware Scanning API for File Uploads	en	information-and-network-security	robots llmsaihumans	emailphone	partial · 8
depsec.dev ↗	65 match 1 shared topics	depsec — Dependency Security Scanner for CI/CD	en	information-and-network-security	robotsllmsaihumans	emailphone	none
sandboxscanner.com ↗	65 match 1 shared topics	SandboxScanner — npm Supply Chain Threat Detection	en	information-and-network-security	robotsllmsaihumans	emailphone	none
zseceye.com ↗	65 match 1 shared topics	ZSecEye — Malware Sample Analysis	en	information-and-network-security	robots llmsaihumans	emailphone	none
delvok.com ↗	65 match 1 shared topics	Delvok - WordPress Malware Rescue	en	information-and-network-security WooCommerce	robotsllmsaihumans	emailphone	none
cyberglobes-anti-influence.com ↗	65 match 1 shared topics	CG - anti-Infulence - website	en	information-and-network-security	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.