similar sites

Browse

Tools

🚀Submit Your Site to AIPush your URL to AI search engines 🤖AI Crawler CheckerSee which AI bots your site blocks 🎯AI Readiness CheckerScore your site 0–100 for AI 🔗Backlink CheckerWho links to any site — free All tools →

Sites similar to ractor.tech

Ractor alternatives & similar sites

Rohit Dongre — AI Security Researcher & Bug Hunter | ractor.tech — 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
aipwn.org ↗	73 match 2 shared topics	AI Security Research	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0xdkay.me ↗	72 match 2 shared topics	Dongkwan Kim \| Security Researcher	en	information-and-network-security	robotsllmsaihumans	emailphone	none
ekagrazi.com ↗	72 match 2 shared topics	Ekagra Gupta — Developer \| AI Engineer \| Security Researcher	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
raoufabedini.dev ↗	71 match 2 shared topics	Mohammad Raouf Abedini \| AI Security Researcher	Australia~ en	information-and-network-security	robots llmsaihumans	emailphone	partial · 8
medullainstitute.org ↗	71 match 2 shared topics	Medulla AI Security Research Institute	United States~ en	artificial-intelligence	robots llmsaihumans	emailphone	partial · 8
0ximu.dev ↗	71 match 2 shared topics	0ximu \| Security Researcher	en	information-and-network-security	robotsllmsaihumans	emailphone	none
htsone.ai ↗	70 match 2 shared topics	HTSOne — Your AI Security Engineer \| Autonomous AppSec	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
agentprivilege.ai ↗	70 match 2 shared topics	Agent Privilege Lab — AI Agent Security Research	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
advancedneuralsecurityresearch.org ↗	70 match 2 shared topics	Advanced Neural Security Research	en	information-and-network-security	robotsllmsaihumans	emailphone	none
sgklabs.com ↗	70 match 2 shared topics	SGK Labs - AI, Blockchain & Robot Security Research	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
agentichardening.ai ↗	69 match 2 shared topics	Agentic Hardening — Curated Agentic AI Security Resources	en	information-and-network-security	robotsllmsaihumans	emailphone	none
egida.ai ↗	69 match 2 shared topics	Egida — AI Security for AI-Built Apps	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
obsidianedge.io ↗	69 match 2 shared topics	Obsidian Edge — AI Security & Adversarial Risk Advisory	en	information-and-network-security	robotsllmsaihumans	emailphone	none
agenthacker.ai ↗	69 match 2 shared topics	AgentHacker \| AI Adversarial Research & Security Engineering	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
mindfizz.ai ↗	69 match 2 shared topics	MindFizz — AI Security & Automation	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
kaustubhchude.com ↗	69 match 2 shared topics	Kaustubh Chude \| Research Engineer & Tech Consultant	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
servailor.com ↗	69 match 2 shared topics	Servailor \| AI Security & Protection Platform	en	information-and-network-security	robotsllmsaihumans	emailphone	none
casky.ai ↗	69 match 2 shared topics	Casky — AI Security Investigation Platform	en	information-and-network-security	robots llmsaihumans	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.