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SkillScanner — Detect Malicious Claude Skills — 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
mcpskills.io ↗	65 match 2 shared topics	MCP Skills — Pre-Install Trust Layer for MCP Servers	en	information-and-network-security	robots llmsaihumans	emailphone	none
badgerwp.com ↗	64 match 2 shared topics	Badger — Don't just block AI bots. Trap them.	en	artificial-intelligence WooCommerce	robotsllmsaihumans	emailphone	none
backerguardian.com ↗	64 match 2 shared topics	BackerGuardian \| Crowdfunding Trust Analysis & Scam Detection	en	artificial-intelligence	robots llmsaihumans	emailphone	none
ferralon.com ↗	64 match 2 shared topics	Ferralon — Autonomous Cyber Remediation	en	information-and-network-security	robotsllmsaihumans	emailphone	none
onfishy.com ↗	64 match 2 shared topics	Fishy - AI-Powered Scam Detection	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
impostorhunter.com ↗	64 match 2 shared topics	ImposterHunter: We detect deception. Any medium. Any method.	United Arab Emirates~ en	artificial-intelligence	robotsllmsaihumans	emailphone	none
imposterhunter.com ↗	64 match 2 shared topics	ImposterHunter: We detect deception. Any medium. Any method.	United Arab Emirates~ en	artificial-intelligence	robotsllmsaihumans	emailphone	none
blackfog.cloud ↗	64 match 2 shared topics	BlackFog AI Security for Data Exfiltration, Shadow AI and Ransomware Prevention	en	information-and-network-security WordPress WooCommerce	robotsllmsaihumans	emailphone	none
coresign.ai ↗	64 match 2 shared topics	Coresign.ai — Cyber risk for LATAM. Detect, remediate, insure.	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
thexar.com ↗	64 match 2 shared topics	thexar — AI Security Evaluation	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
aapt.online ↗	64 match 2 shared topics	AAPT — AI Agent Penetration Testing \| LLM, MCP & GraphQL Security	en	information-and-network-security	robots llmsaihumans	emailphone	none
mdr-guardians.digital ↗	64 match 2 shared topics	Sophos MDR \| 24/7 Managed Detection & Response \| Agentic SOC	en	information-and-network-security	robotsllmsaihumans	emailphone	none
mdr-guardians.io ↗	64 match 2 shared topics	Sophos MDR \| 24/7 Managed Detection & Response \| Agentic SOC	en	information-and-network-security	robotsllmsaihumans	emailphone	none
mdrguardians.app ↗	64 match 2 shared topics	Sophos MDR \| 24/7 Managed Detection & Response \| Agentic SOC	en	information-and-network-security	robotsllmsaihumans	emailphone	none
mdrguardians.io ↗	64 match 2 shared topics	Sophos MDR \| 24/7 Managed Detection & Response \| Agentic SOC	en	information-and-network-security	robotsllmsaihumans	emailphone	none
langguard.ai ↗	64 match 2 shared topics	LangGuard — Deterministic Runtime AI Governance \| LangGuard - Deterministic Runtime AI Governance Platform	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
blackmatterdefense.com ↗	63 match 2 shared topics	Black Matter Defense — Enterprise AI Security Consultancy	en	information-and-network-security	robotsllmsaihumans	emailphone	none
fense.ai ↗	63 match 2 shared topics	Fense.ai - Advanced E-commerce Fraud Detection and Prevention	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.