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Sites similar to freeenforceauth.com

Freeenforceauth alternatives & similar sites

EnforceAuth — Authorization for the AI agent 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
enforceauth.com ↗	85 match shared topic	EnforceAuth — Authorization for the AI agent era	en	artificial-intelligence Sanity	robots llmsaihumans	emailphone	none
hoop.dev ↗	70 match shared topic	hoop.dev \| Accelerate your AI agents. One gateway to every data source.	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
swimlane.com ↗	70 match shared topic	Swimlane: Agentic AI Security Automation, Hyperautomation, SOC Automation	United States~ en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
auth0.com ↗	62 match shared topic	Secure AI Agent & User Authentication \| Auth0	United States~ en	artificial-intelligence	robots llmsaihumans	emailphone	none
tenable.com ↗	62 match shared topic	Vulnerability and exposure management \| Cloud and AI security \| Tenable®	en	information-and-network-security Drupal	robotsllmsaihumans	emailphone	none
snyk.io ↗	62 match shared topic	Snyk AI Security Fabric \| Secure Code, Models & Agents \| Snyk	en	information-and-network-security	robotsllmsaihumans	emailphone	none
arcticwolf.com ↗	62 match shared topic	A Higher Standard of Security Operations \| Arctic Wolf	en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
endorlabs.com ↗	62 match shared topic	Endor Labs \| Agentic Application Security Platform	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
snyk.co ↗	62 match shared topic	Snyk AI Security Fabric \| Secure Code, Models & Agents \| Snyk	Colombia en	information-and-network-security	robotsllmsaihumans	emailphone	none
trmlabs.com ↗	62 match shared topic	TRM Labs \| Agents and intelligence to fight crime	United States~ en	information-and-network-security	robots llmsaihumans	emailphone	none
securityaudit.dev ↗	62 match shared topic	Security Audit AI Agent	en	information-and-network-security	robotsllmsaihumans	emailphone	none
descope.com ↗	62 match shared topic	Descope \| Customer and Agentic Identity Platform	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
aembit.io ↗	62 match shared topic	Aembit \| Agentic AI and Workload Identity & Access Management	en	information-and-network-security WordPress Lightspeed	robots llmsaihumans	emailphone	none
privasee.io ↗	62 match shared topic	AI Security Questionnaire & RFP Automation \| Vera	en	artificial-intelligence	robotsllmsaihumans	email phone	none
salt.security ↗	62 match shared topic	Salt Security: Agentic AI Security, MCP Discovery, and API Security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
ai-alert.org ↗	62 match shared topic	AI Alert — AI Incident & ML Vulnerability Tracking	en	information-and-network-security	robots llmsaihumans	emailphone	none
moltaicorp.com ↗	62 match shared topic	Molt AI \| Adversarial Testing and Assurance for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
daytona.io ↗	62 match shared topic	Daytona - Secure Infrastructure for Running AI-Generated Code	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.