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Aidefense alternatives & similar sites

AI Defense — Guardrails & Model Hardening for LLMs — 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
proxy0.dev ↗	68 match 2 shared topics	proxy0 - Guardrails for AI Agents	en	artificial-intelligence Spree Commerce	robotsllmsaihumans	emailphone	none
attackbranch.com ↗	67 match 2 shared topics	AttackBranch — AI threat modeling for modern architectures	en	information-and-network-security	robots llmsaihumans	emailphone	none
1defender.ai ↗	65 match 2 shared topics	1Defender Platform — One AI. Every cloud. Every defense.	en	information-and-network-security	robotsllmsaihumans	emailphone	none
1id.com ↗	65 match 2 shared topics	1id.com — Hardware-Backed Identity for AI Agents & Relying Parties	en	information-and-network-security	robots llmsaihumans	emailphone	none
vordr-mindgrid.com ↗	65 match 2 shared topics	VORDR MindGrid \| Cognitive Defense Division	en	information-and-network-security	robotsllmsaihumans	email phone	none
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 ↗	64 match 2 shared topics	Ethiack — Autonomous Ethical Hacking for continuous security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
doppelforge.com ↗	64 match 2 shared topics	DoppelForge - Obfuscate API Responses for LLMs	en	information-and-network-security	robotsllmsaihumans	emailphone	none
llmforcyber.com ↗	64 match 2 shared topics	LLM for Cyber \| Improving Cybersecurity with LLMs	en	information-and-network-security Spree Commerce	robotsllmsaihumans	emailphone	none
skyshieldtechnology.com ↗	64 match 2 shared topics	SkyShield Technology \| AI-Powered Cybersecurity & Autonomous Defense	en	information-and-network-security	robotsllmsaihumans	emailphone	none
vordrmindgrid.com ↗	64 match 2 shared topics	VORDR International Cognitive Defense	en	information-and-network-security	robots llmsaihumans	emailphone	none
provenlog.com ↗	64 match 2 shared topics	ProvenLog — Tamper-evident audit trails for AI agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0eroshot.com ↗	64 match 2 shared topics	ZeroShot — Offensive Security Testing for AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
atomicslicearchitecture.org ↗	64 match 2 shared topics	ASA — AI Safe Architecture	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
atomicslicearchitecture.com ↗	64 match 2 shared topics	ASA — AI Safe Architecture	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
voicesecurity.org ↗	64 match 2 shared topics	Deepfake Defense for Calls, Virtual Meetings, & Contact Centers \| Pindrop	en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
provenyx.ai ↗	64 match 2 shared topics	Provenyx — AI Access Control for Your Company Files	en	artificial-intelligence Ghost	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.