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Underfl0W alternatives & similar sites

Underfl0w's infosec corner — 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
0xkayala.com ↗	68 match 1 shared topics	Satya Prakash \| InfoSec Portfolio	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
incidentalinfosec.com ↗	67 match 1 shared topics	Incidental InfoSec Blog	en	information-and-network-security	robotsllmsaihumans	emailphone	none
thisisgrc.com ↗	66 match 1 shared topics	Cybersecurity Jokes \| The Funniest InfoSec Humor on the Internet	en	information-and-network-security	robotsllmsaihumans	emailphone	none
sandenaw.com ↗	66 match 1 shared topics	Sandenaw Infosec - Your Partner in Information Security Solutions	en	information-and-network-security Weebly	robotsllmsaihumans	emailphone	none
netforensics.co.uk ↗	66 match 1 shared topics	Home \| Information security consultants \| Cyberis Reply Limited	United Kingdom en	information-and-network-security	robotsllmsaihumans	emailphone	none
demtechgroup.eu ↗	65 match 1 shared topics	CISAT - Center for Information Security and Trust	European Union en	information-and-network-security	robotsllmsaihumans	emailphone	none
0x-id.info ↗	65 match 1 shared topics	NullSec - Underground Security Forum	en	information-and-network-security	robotsllmsaihumans	emailphone	none
blackhilsinfosec.com ↗	65 match 1 shared topics	BHIS - Black Hills Information Security, Inc.	en	information-and-network-security WordPress Shopify	robotsllmsaihumans	emailphone	none
blackhillsinfosec.com ↗	65 match 1 shared topics	BHIS - Black Hills Information Security, Inc.	en	information-and-network-security WordPress Shopify	robotsllmsaihumans	emailphone	none
blackhillsinformationsecurity.com ↗	65 match 1 shared topics	BHIS - Black Hills Information Security, Inc.	en	information-and-network-security WordPress Shopify	robotsllmsaihumans	emailphone	none
cybersecforum.eu ↗	65 match 1 shared topics	CYBERSEC - European Cybersecurity Forum	European Union en	information-and-network-security	robotsllmsaihumans	email phone	none
blackethics.dev ↗	65 match 1 shared topics	Md Abu Saeed \| Penetration Tester & Security Researcher	en	information-and-network-security	robotsllmsaihumans	emailphone	none
badprofessor.com ↗	64 match 1 shared topics	Joshua Morgan - Information Security Professional and Instructor — ilovesec	en	information-and-network-security	robotsllmsaihumans	emailphone	none
corak.io ↗	64 match 1 shared topics	Daniel Corak - Founder & Security Researcher	en	information-and-network-security	robotsllmsaihumans	emailphone	none
improveyourseclife.com ↗	64 match 1 shared topics	Joshua Morgan - Information Security Professional and Instructor — ilovesec	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0deepresearch.com ↗	64 match 1 shared topics	0DeepResearch Insights	en	information-and-network-security	robotsllmsaihumans	emailphone	none
copperriverit.com ↗	64 match 1 shared topics	Copper River Information Technology \| Federal Data Center	en	information-and-network-security WordPress	robotsllmsaihumans	email phone	none
felsuma.com ↗	64 match 1 shared topics	SharpSec - Professional Penetration Testing Services	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.