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UTRAX | Discord Security, Server Builds and Custom Bots for Web3 — 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
joetiedeman.com ↗	66 match 2 shared topics	Joe Tiedeman – Technology and Security	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
csanchez.dev ↗	66 match 2 shared topics	CSanchezAustin \| Musings and experiments on Identity, DevOps, and Security.	en	information-and-network-security	robotsllmsaihumans	emailphone	none
symybau.com ↗	66 match 2 shared topics	symybau - System Updates for Device Security and Performance	en	information-and-network-security	robotsllmsaihumans	emailphone	none
deneyed.com ↗	66 match 2 shared topics	denEyed \| Hacker Minded Security, Made Simple.	en	information-and-network-security	robotsllmsaihumans	emailphone	none
fbupdates.com ↗	66 match 2 shared topics	FBUpdates \| Cybersecurity, Technology News and Support	en	technology-and-computing	robotsllmsaihumans	emailphone	partial · 3
8bitsecurity.com ↗	66 match 2 shared topics	Home \| 8Bit Security	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
nawilson.com ↗	66 match 2 shared topics	dc=nawilson,dc=com \| LDAP, programming, security, movies, and other stuff	en	technology-and-computing WordPress	robotsllmsaihumans	emailphone	none
cy-brush.com ↗	66 match 2 shared topics	Cybrush - Practical Cybersecurity for Everyone	en	information-and-network-security	robotsllmsaihumans	emailphone	none
1percentnerd.com ↗	66 match 2 shared topics	Ezekiel A. Obeisun Jr \| Security Analyst \| AWS Community Builder \| NerdPioneer	US~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
delaender.net ↗	66 match 2 shared topics	Jelle De Laender — Security Leader & Founder of Coding Mammoth	en	information-and-network-security	robots llms ai humans	email phone	none
favourori.com ↗	66 match 2 shared topics	Favour Ori \| Senior Security Engineer	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
joeelhousseini.com ↗	66 match 2 shared topics	Joe El Housseini - Tech, Cybersecurity, and more	en	technology-and-computing WordPress	robotsllmsaihumans	emailphone	none
joshhixson.com ↗	66 match 2 shared topics	Cyber Security Today: Essential Lifehacks for Enhanced Computer Security	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
cryptoinheritance.org ↗	65 match 2 shared topics	Coinkite: Bitcoin Security and Fun Devices	en	technology-and-computing	robotsllmsaihumans	emailphone	none
cyberhatlab.cfd ↗	65 match 2 shared topics	Cyber Security Lab	en	information-and-network-security	robotsllmsaihumans	emailphone	none
usepyre.com ↗	65 match 2 shared topics	Pyre — Review layer for GitHub Security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
hashlock.com ↗	65 match 2 shared topics	Smart Contract Audits & Blockchain Security \| Hashlock	AU~ en	information-and-network-security WordPress	robots llmsaihumans	emailphone	partial · 8
decoder.cloud ↗	65 match 2 shared topics	Decoder's Blog – IT Security Tips and Tricks	en	information-and-network-security WordPress	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.