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Vulcn alternatives & similar sites

Vulcn — Security evals for the AI era — 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
tenable.com ↗	75 match shared topic	Vulnerability and exposure management \| Cloud and AI security \| Tenable®	en	information-and-network-security Drupal	robotsllmsaihumans	emailphone	none
arcticwolf.com ↗	75 match shared topic	A Higher Standard of Security Operations \| Arctic Wolf	en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
privasee.io ↗	75 match shared topic	AI Security Questionnaire & RFP Automation \| Vera	en	artificial-intelligence	robotsllmsaihumans	email phone	none
esentire.com ↗	75 match shared topic	Managed Detection and Response Services & Security Operations Platform \| eSentire	en	information-and-network-security	robots llmsaihumans	email phone	partial · 9
lakera.ai ↗	75 match shared topic	Lakera: The AI-Native Security Platform to Accelerate GenAI	en	information-and-network-security	robotsllmsaihumans	emailphone	none
pushsecurity.com ↗	75 match shared topic	Browser Security for the AI Era \| Push Security	en	information-and-network-security	robots llmsaihumans	emailphone	none
cyera.com ↗	75 match shared topic	AI Security Platform \| Protect Data & Secure AI \| Cyera	en	artificial-intelligence	robots llmsaihumans	emailphone	none
swimlane.com ↗	75 match shared topic	Swimlane: Agentic AI Security Automation, Hyperautomation, SOC Automation	United States~ en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
techaro.lol ↗	65 match shared topic	Techaro — Security Software & AI Consultancy	en	information-and-network-security	robotsllmsaihumans	emailphone	none
hackerone.com ↗	65 match shared topic	HackerOne \| Leader in Continuous Threat Exposure Management \| Security for AI	en	information-and-network-security Drupal	robotsllmsaihumans	emailphone	none
sentinelone.com ↗	65 match shared topic	SentinelOne \| AI-Powered Enterprise Cybersecurity Platform	en	information-and-network-security	robots llmsaihumans	emailphone	none
snyk.io ↗	65 match shared topic	Snyk AI Security Fabric \| Secure Code, Models & Agents \| Snyk	en	information-and-network-security	robotsllmsaihumans	emailphone	none
que.com ↗	65 match shared topic	QUE.com - Artificial Intelligence Machine Learning CyberSecurity Robotics Blockchain	en	artificial-intelligence WordPress WooCommerce	robots llmsaihumans	emailphone	none
securitypal.com ↗	65 match shared topic	Cybersecurity Assurance Management Platform: AI + Certified Experts \| SecurityPal AI	United States~ en	information-and-network-security HubSpot CMS	robotsllmsaihumans	emailphone	none
forcepoint.com ↗	65 match shared topic	Forcepoint: The #1 AI Data Security Platform	en	information-and-network-security Drupal	robotsllmsaihumans	emailphone	none
verkada.com ↗	65 match shared topic	Security Systems for the Modern Enterprise \| Verkada	en	information-and-network-security	robotsllmsaihumans	emailphone	none
wiz.io ↗	65 match shared topic	Wiz: AI Cybersecurity for All Your Cloud and AI Applications	en	information-and-network-security DatoCMS	robotsllmsaihumans	emailphone	none
darktrace.com ↗	65 match shared topic	Darktrace \| The Essential AI Cybersecurity Platform	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.