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Smart Contract Audits by SourceHat — 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
blockchainlabs.tech ↗	81 match 1 shared topics	Smart Contract Audits	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0xwalterwhitehat.com ↗	77 match 1 shared topics	0xWalterWhiteHat \| Smart Contract Auditor	en	information-and-network-security	robotsllmsaihumans	emailphone	none
bailsec.io ↗	75 match 1 shared topics	Smart Contract Audits & Web3 Security \| BailSec	en	information-and-network-security	robotsllmsaihumans	emailphone	none
blockvigil.io ↗	74 match 1 shared topics	Smart Contract Audit & Web3 Security Firm \| BlockVigil	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	full · 15
thewolfsec.com ↗	73 match 1 shared topics	WolfSec — EVM Smart Contract Security Audits	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0xram.com ↗	73 match 1 shared topics	0xRAM Labs \| Tier-1 Smart Contract Auditing & Web3 Cybersecurity	en	information-and-network-security	robotsllmsaihumans	emailphone	none
block08.com ↗	72 match 1 shared topics	Block08 Security Audits \| Smart Contract Security & Blockchain Auditing	en	information-and-network-security	robotsllmsaihumans	emailphone	none
cqr.company ↗	69 match 1 shared topics	CQR \| Cybersecurity Services \| Penetration Testing \| Smart Contract Audit \| Blockchain Security	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
mckinleysinternational.com ↗	68 match 1 shared topics	McKinley's Technologies \| Smart Contract Audit and Blockchain Security Firm	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0xweiss.com ↗	66 match 1 shared topics	0xWeiss - Security Researcher & Auditor	en	information-and-network-security	robotsllmsaihumans	emailphone	none
blocksec.tech ↗	66 match 1 shared topics	Web3 Security Audits, Monitoring, and Risk Prevention - BlockSec	en	information-and-network-security	robots llmsaihumans	emailphone	none
rcesecurity.eu ↗	66 match 1 shared topics	RCE Security \| Penetration Tests. Source Code Reviews. IT Security Audits.	European Union en	information-and-network-security	robotsllmsaihumans	emailphone	none
rce-security.eu ↗	66 match 1 shared topics	RCE Security \| Penetration Tests. Source Code Reviews. IT Security Audits.	European Union en	information-and-network-security	robotsllmsaihumans	emailphone	none
1sourcedigital.com ↗	66 match 1 shared topics	Home - One Source Digital Technologies	en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
impalabs.com ↗	66 match 1 shared topics	Impalabs - Security Audits, Consulting and Training	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0xlabs.ai ↗	65 match 1 shared topics	0xLabs \| Web3 Security Audit Platform	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
4access.io ↗	65 match 1 shared topics	4Access \| South African Access Control Solutions	en	information-and-network-security	robotsllmsaihumans	emailphone	none
spl0it.org ↗	65 match 1 shared topics	Welcome to spl0it.org \| Open Source Security Tools by Joshua "Jabra" Abraham	en	information-and-network-security	robotsllmsaihumans	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.