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Bangla Natesha | Cybersecurity Researcher & Offensive Security Specialist — 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
0xpolar.com ↗	82 match 1 shared topics	0xpolar - Cybersecurity Research & Offensive Security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
acrox.space ↗	78 match 1 shared topics	ACRO — Cybersecurity Researcher & Tool Builder	en	information-and-network-security	robotsllmsaihumans	emailphone	none
cyburton.io ↗	75 match 1 shared topics	Cyburton \| Offensive Cybersecurity Specialists \| Think like an attacker. Defend like a pro.	en	information-and-network-security Squarespace Magento	robotsllmsaihumans	emailphone	none
4cybersecurity.com ↗	75 match 1 shared topics	4CyberSecurity -- Specialized Cyber Security Search Engine	en	information-and-network-security	robotsllmsaihumans	emailphone	none
keepernet.io ↗	75 match 1 shared topics	Keepernet - Offensive Cybersecurity	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
sterva.org ↗	75 match 1 shared topics	Sterva - Security Researcher & Developer	en	information-and-network-security	robotsllmsaihumans	emailphone	none
abhinavverma.codes ↗	75 match 1 shared topics	Abhinav Verma - Cybersecurity Engineer & Digital Defense Specialist	en	information-and-network-security	robotsllmsaihumans	emailphone	none
deathangelsec.com ↗	74 match 1 shared topics	DeathAngel Security — Cybersecurity Services	en	information-and-network-security Gumroad	robotsllmsaihumans	emailphone	none
n3sec.com ↗	74 match 1 shared topics	N3 Sec - Cybersecurity Specialist	en	information-and-network-security	robotsllmsaihumans	emailphone	none
manishreddy.online ↗	74 match 1 shared topics	Manish Reddy Koduri - Cybersecurity Professional \| Security Analyst \| Researcher	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0xdigi.com ↗	74 match 1 shared topics	0xdigi — Cybersecurity & Offensive Tools	en	information-and-network-security	robotsllmsaihumans	emailphone	none
reversense.com ↗	74 match 1 shared topics	Reversense - Offensive cybersecurity solutions for security experts	en	information-and-network-security HubSpot	robotsllmsaihumans	emailphone	none
abderrahimhb.site ↗	74 match 1 shared topics	Abderrahime Elhammou Brahimi — Cybersecurity Specialist	en	information-and-network-security	robotsllmsaihumans	email phone	none
0xamr.com ↗	74 match 1 shared topics	Amr Al Hallak \| Cybersecurity & Bug Bounty	en	information-and-network-security	robotsllmsaihumans	email phone	none
0xweiss.com ↗	74 match 1 shared topics	0xWeiss - Security Researcher & Auditor	en	information-and-network-security	robotsllmsaihumans	emailphone	none
william-hays.com ↗	73 match 1 shared topics	William Hays \| Cybersecurity & Security Operations	en	information-and-network-security	robotsllmsaihumans	emailphone	none
defenzo.ai ↗	73 match 1 shared topics	Defenzo Cyber Tech -FZCO \| Offensive Security & Incident Response	United Arab Emirates~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
nagareyash.com ↗	73 match 1 shared topics	Yash Nagare — Cybersecurity Engineer & Researcher	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.