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Attackbranch alternatives & similar sites

AttackBranch — AI threat modeling for modern architectures — 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
atomicslicearchitecture.org ↗	71 match 2 shared topics	ASA — AI Safe Architecture	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
atomicslicearchitecture.com ↗	71 match 2 shared topics	ASA — AI Safe Architecture	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
3mpath.net ↗	68 match 2 shared topics	3mpath — AI-Cybersecurity Architect	en	information-and-network-security	robotsllmsaihumans	emailphone	none
horusguardian.tech ↗	67 match 2 shared topics	Horus Guardian — AI Threat Detection	en	information-and-network-security Spree Commerce	robotsllmsaihumans	emailphone	none
365architect.com ↗	67 match 2 shared topics	Securing Enterprise Architecture in the AI Era \| 365 Architect	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
atelamind.com ↗	67 match 2 shared topics	AtelaMind \| Enterprise AI Architecture, Security & Assurance	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
vortib.com ↗	67 match 2 shared topics	Vortib AI — AI-Powered IoT Threat Detection	en	information-and-network-security	robotsllmsaihumans	emailphone	none
attack-vector.com ↗	66 match 2 shared topics	Attack-Vector – AI-Powered Cyber Threat Intelligence	en	information-and-network-security Spree Commerce	robotsllmsaihumans	emailphone	none
neoauth.com ↗	66 match 2 shared topics	NeoAuth \| Facial Intelligence for the Modern, Threat-Rich World	en	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 11
astraqcyberdefence.com ↗	65 match 2 shared topics	AstraQ Cyber Defence — AI-Native Security & Intelligence for Modern Enterprises	India~ en	information-and-network-security	robotsllmsaihumans	email phone	none
autonomousethicalhacking.com ↗	65 match 2 shared topics	Ethiack — Autonomous Ethical Hacking for continuous security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
sitrepit.com ↗	65 match 2 shared topics	SitRep — AI Intelligence Briefing for Security Teams	en	information-and-network-security	robotsllmsaihumans	emailphone	none
provenyx.ai ↗	65 match 2 shared topics	Provenyx — AI Access Control for Your Company Files	en	artificial-intelligence Ghost	robotsllmsaihumans	emailphone	none
sksecurity.io ↗	65 match 2 shared topics	SKSecurity — The Security Scanner That Sees AI Threats	en	information-and-network-security	robots llmsaihumans	emailphone	partial · 8
0eroshot.com ↗	65 match 2 shared topics	ZeroShot — Offensive Security Testing for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
protostars.ai ↗	65 match 2 shared topics	Protostars.ai — AI Trust Infrastructure for EU Cyber Resilience Act	en	information-and-network-security	robotsllmsaihumans	emailphone	none
vorty-nex.com ↗	65 match 2 shared topics	VORTYNEX \| AI-Powered Control for Modern IT	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
cupnstring.com ↗	64 match 2 shared topics	Cup'n'String — AI Agent Security Control Plane for MCP, Local Runtimes & Developer Workstations	en	information-and-network-security	robots llmsaihumans	emailphone	partial · 8

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.