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Voicesunhidden alternatives & similar sites

Voices Unhidden™ | Technology-Facilitated Harassment & Stalking (TFHS) — 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
cybersafetywatchdog.org ↗	62 match 2 shared topics	Home	en	information-and-network-security Weebly	robotsllmsaihumans	emailphone	none
phintic.com ↗	62 match 2 shared topics	Phintic - Cybersecurity Made Simple	en	information-and-network-security	robotsllmsaihumans	emailphone	none
serapsecure.com ↗	62 match 2 shared topics	Seraph Secure - Anti Scam Protection for Online Scams	en	information-and-network-security	robotsllmsaihumans	emailphone	none
seraphssecure.com ↗	62 match 2 shared topics	Seraph Secure - Anti Scam Protection for Online Scams	en	information-and-network-security	robotsllmsaihumans	emailphone	none
seraphsecured.com ↗	62 match 2 shared topics	Seraph Secure - Anti Scam Protection for Online Scams	en	information-and-network-security	robotsllmsaihumans	emailphone	none
seraphsecure.com ↗	62 match 2 shared topics	Seraph Secure - Anti Scam Protection for Online Scams	en	information-and-network-security	robotsllmsaihumans	emailphone	none
seraphsecur.com ↗	62 match 2 shared topics	Seraph Secure - Anti Scam Protection for Online Scams	en	information-and-network-security	robotsllmsaihumans	emailphone	none
seraphhsecure.com ↗	62 match 2 shared topics	Seraph Secure - Anti Scam Protection for Online Scams	en	information-and-network-security	robotsllmsaihumans	emailphone	none
seraph-secure.com ↗	62 match 2 shared topics	Seraph Secure - Anti Scam Protection for Online Scams	en	information-and-network-security	robotsllmsaihumans	emailphone	none
serahpsecure.com ↗	62 match 2 shared topics	Seraph Secure - Anti Scam Protection for Online Scams	en	information-and-network-security	robotsllmsaihumans	emailphone	none
serifsecure.com ↗	62 match 2 shared topics	Seraph Secure - Anti Scam Protection for Online Scams	en	information-and-network-security	robotsllmsaihumans	emailphone	none
serphsecure.com ↗	62 match 2 shared topics	Seraph Secure - Anti Scam Protection for Online Scams	en	information-and-network-security	robotsllmsaihumans	emailphone	none
cleanbrowsing.org ↗	62 match 2 shared topics	CleanBrowsing \| DNS Content Filtering Service	en	information-and-network-security	robots llmsaihumans	emailphone	none
cyberpeace.global ↗	62 match 2 shared topics	CyberPeace Corps \| A global movement to secure the digital world!	en	information-and-network-security	robotsllmsaihumans	emailphone	none
cybersafety.ngo ↗	62 match 2 shared topics	KnowledgeFlow Cybersafety Foundation \| Home Page	en	information-and-network-security WordPress WooCommerce	robotsllmsaihumans	emailphone	partial · 8
cybersafety.foundation ↗	62 match 2 shared topics	KnowledgeFlow Cybersafety Foundation \| Home Page	en	information-and-network-security WordPress WooCommerce	robotsllmsaihumans	emailphone	none
qvpn.io ↗	62 match 2 shared topics	QVPN - Privacy-First VPN \| Fast & Secure	en	information-and-network-security	robotsllmsaihumans	emailphone	none
catdams.ai ↗	62 match 2 shared topics	CATDAMS - AI Safety & Threat Detection \| Protect Families & Organizations from Harmful AI Interactions	United States~ 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.