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Riot Security Team - Vulnerability Research & Responsible Disclosure — 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
stationedk06.dev ↗	68 match 2 shared topics	Joohan Kim — Security Research & CTF Writeups	en	information-and-network-security	robotsllmsaihumans	emailphone	none
window.events ↗	68 match 2 shared topics	Window Events – Security Research & CTF Writeups	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
malicious.pro ↗	68 match 2 shared topics	Malicious.pro — Security Researcher	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0xsabre.tech ↗	68 match 2 shared topics	Security Researcher - I'm 0xsabre — pentester, vulnerability researcher, and occasional CVE contributor. This is where I write about breaking things responsibly.	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
stackshield.io ↗	68 match 2 shared topics	Laravel Security Monitoring & Vulnerability Scanner \| StackShield	en	information-and-network-security	robots llmsaihumans	emailphone	partial · 7
thesandf.com ↗	68 match 2 shared topics	thesandf \| Smart Contract Security Researcher	en	information-and-network-security	robotsllmsaihumans	emailphone	none
khirawdhi.com ↗	67 match 2 shared topics	Khirawdhi – Security Researcher & Storyteller	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
sscv-framework.org ↗	67 match 2 shared topics	SSCV Framework - Contextual Vulnerability Risk Scoring \| System Security Context Vector	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0xmaruf.com ↗	67 match 2 shared topics	0xmaruf — Security Researcher & Bug Bounty Hunter	en	information-and-network-security WordPress Spree Commerce	robotsllmsaihumans	emailphone	none
reportizflow.com ↗	66 match 2 shared topics	CVEs and Security Vulnerabilities CVEs and Security Vulnerabilities - OpenCVE	en	information-and-network-security	robotsllmsaihumans	emailphone	none
3ziz.me ↗	66 match 2 shared topics	Abdulaziz Almadhi · Offensive Security Researcher \| 3ziz.me	en	information-and-network-security	robots llmsaihumans	email phone	none
threatmine.io ↗	66 match 2 shared topics	threatmine.io – Cyber Threat Intel \| Security Research \| Data Science	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
deadhacker.com ↗	66 match 2 shared topics	deadhacker.com – security research repository of nathan andrew fain / cyphunk	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
kidneyweakx.com ↗	66 match 2 shared topics	NEO_TOKYO TERMINAL // kidneyweakx - Web3 Developer & Security Researcher	en	technology-and-computing	robotsllmsaihumans	emailphone	none
algiz.biz ↗	65 match 2 shared topics	Algiz — Internal & External Vulnerability Scanning	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
0xsp.com ↗	65 match 2 shared topics	Game of Hide and Seek: Detecting Dynamic API Resolution at Runtime With Aether - 0xsp SRD - Security Research & Development	en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
defectdojo.com ↗	65 match 2 shared topics	DefectDojo: Open-Source Vulnerability Management and ASPM	en	information-and-network-security HubSpot	robotsllmsaihumans	emailphone	none
kevintel.com ↗	65 match 2 shared topics	KEVIntel — Real-Time Exploited Vulnerability Intelligence	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.