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Neobotnet alternatives & similar sites

neobotnet — mapping the web from an attacker's view — 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
defendra.dev ↗	67 match 1 shared topics	Defendra — Domain Attack-Surface Scanner (Email + Web)	en	information-and-network-security	robots llmsaihumans	emailphone	none
kanfrancisco.com ↗	67 match 1 shared topics	APP SECURITY INSIGHTS - Discover security weaknesses from an attacker’s perspective	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	partial · 1
tritanium.ai ↗	66 match 1 shared topics	Tritanium.ai — Cyber Attack Prevention Platform for the AI Era	Australia~ en	information-and-network-security	robots llmsaihumans	emailphone	none
amapd.com ↗	66 match 1 shared topics	AmapD - MITRE ATT&CK Mapping Tool \| Attack to Defence Controls Simplified	en	information-and-network-security	robots llmsaihumans	emailphone	partial · 8
defendxtech.com ↗	66 match 1 shared topics	Securing the Future — Intelligently	en	information-and-network-security	robotsllmsaihumans	emailphone	none
mcpscanner.dev ↗	66 match 1 shared topics	MCP Scanner — Scan your MCP servers before attackers do. · by codelake	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
mcpscanner.app ↗	66 match 1 shared topics	MCP Scanner — Scan your MCP servers before attackers do. · by codelake	en	information-and-network-security	robotsllmsaihumans	emailphone	none
cyburton.io ↗	66 match 1 shared topics	Cyburton \| Offensive Cybersecurity Specialists \| Think like an attacker. Defend like a pro.	en	information-and-network-security Squarespace Magento	robotsllmsaihumans	emailphone	none
iconsoftheweb.com ↗	65 match 1 shared topics	Icons of the Web	en	information-and-network-security	robotsllmsaihumans	emailphone	none
sicenter.io ↗	65 match 1 shared topics	SICenter — See every exposure before attackers do	en	information-and-network-security	robotsllmsaihumans	emailphone	none
flawatch.com ↗	65 match 1 shared topics	Flawatch \| Real-Time Attack Surface Management	en	information-and-network-security	robotsllmsaihumans	emailphone	none
flyto2.com ↗	65 match 1 shared topics	Evidence-backed CTEM for attack surface, dark web, and code risk — Flyto2	en	information-and-network-security	robots llmsaihumans	emailphone	partial · 16
dcshadow.com ↗	65 match 1 shared topics	DCShadow attack	en	information-and-network-security	robotsllmsaihumans	emailphone	none
breaking-the-code.com ↗	65 match 1 shared topics	Breaking the Code	en	information-and-network-security	robotsllmsaihumans	emailphone	none
defensehorizon.com ↗	65 match 1 shared topics	Navigating the world of information security	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
deepblueteam.com ↗	64 match 1 shared topics	Deepblue - Uncover the gaps attackers would exploit	en	information-and-network-security	robots llmsaihumans	emailphone	none
0xspectra.com ↗	64 match 1 shared topics	0xSpectra — Understanding the structures beneath the signals	en	information-and-network-security	robotsllmsaihumans	emailphone	none
9phut.org ↗	64 match 1 shared topics	9phut — Enter The Void	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.