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Securityelites alternatives & similar sites

Securityelites — AI Red Team Learning Platform — 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 Artificial Intelligence →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
kraseawa.com ↗	50 match 2 shared topics	KRASE AWA — AI Security Governance Platform	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
volkankutal.com ↗	50 match 2 shared topics	Volkan Kutal - Agentic AI Red Teaming & Security Validation	Germany~ en	artificial-intelligence	robotsllmsaihumans	emailphone	none
krak-ai.com ↗	50 match 2 shared topics	KRAK AI - LLM Security Testing Platform	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
korosen.com ↗	50 match 2 shared topics	Korosen - Your Personalised AI Learning Platform	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
backslash.security ↗	48 match 2 shared topics	Backslash \| Agentic AI Endpoint Security Platform	en	information-and-network-security Webflow	robotsllmsaihumans	emailphone	none
voicesbylisa.com ↗	48 match 2 shared topics	Red Team Operations & Offensive Security Testing \| AI Red Teaming Australia \| Frontier Cyber	Australia~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
herdsecurityio.com ↗	48 match 2 shared topics	Herd Security — The AI Creative Platform for Security Training	en	artificial-intelligence Sanity	robotsllmsaihumans	emailphone	partial · 8
herdsecurity.io ↗	48 match 2 shared topics	Herd Security — The AI Creative Platform for Security Training	en	artificial-intelligence Sanity	robotsllmsaihumans	emailphone	none
devrand.org ↗	48 match 2 shared topics	Gavin Black, PhD — AI/ML Security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
kpnsecuritykpn.com ↗	47 match 2 shared topics	Wallarm \| AI Control Platform — Secure Every AI Workload	United States~ en	artificial-intelligence Webflow	robotsllmsaihumans	emailphone	none
meetcoramai.org ↗	47 match 2 shared topics	Coram: Unified Physical Security Platform	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0xhunter.io ↗	47 match 2 shared topics	0xHunter - Continous Security Platform	en	information-and-network-security	robotsllmsaihumans	emailphone	none
connectendorlabs.com ↗	47 match 2 shared topics	Endor Labs \| AI-Native Application Security Platform	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
360sec.com ↗	47 match 2 shared topics	AI-Powered Cybersecurity Services — MDR, Red Teaming & AI Security Testing \| 360 Security Group	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
kratosphereai.com ↗	47 match 2 shared topics	Agentic AI Cybersecurity Platform \| KratosphereAI	en	information-and-network-security	robotsllmsaihumans	emailphone	none
mordavid.com ↗	47 match 2 shared topics	MOR DAVID - Penetration Tester \| AI Cyber Operator \| Cyber Security Expert \| Team Leader \| Red Team	en	information-and-network-security	robotsllmsaihumans	emailphone	none
paig.ai ↗	47 match 2 shared topics	AI Agent Security & Data Governance Platform \| Trust3 AI	en	artificial-intelligence WordPress	robots llmsaihumans	emailphone	none
heyaicarly.com ↗	47 match 2 shared topics	aiCarly — Learning AI in Public	en	artificial-intelligence	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.