Security Scan Report: uni-lab-rosy.vercel.app

Submitted: Jul 3, 2026, 12:45:28 AMCompleted: Jul 3, 2026, 12:48:38 AMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 2 HTTP transactions. The main domain is uni-lab-rosy.vercel.app and was registered NaN years ago.

Submitted URL: https://uni-lab-rosy.vercel.app/explore/pools/ethereum/0xe63e32b2ae40601662f760d6bf5d771057324fbd97784fe1d3717069f7b75d45

AI Security Verdict

High Risk

Confidence: 99%

7
Risk Score

AI analysis skipped: HTTP 404 error page with no meaningful content to analyze.

Domain age information unavailable

Details

Page Title

404: NOT_FOUND

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

documentation technical

(78%)

Domain Information

You're looking at domain 'uni-lab-rosy.vercel.app' on the application-focused generic top-level domain (.app); it also runs on subdomain 'uni-lab-rosy'. The second-level label 'vercel' is 6 characters long split between two vowels and 4 consonants. Breaking it apart gives two words: ver, cel. Median word length is three characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://uni-lab-rosy.vercel.app/explore/pools/ethereum/0xe63e32b2ae40601662f760d6bf5d771057324fbd97784fe1d3717069f7b75d45

Page Load Overview

9.41s
Total Load Time
2
HTTP Requests
1
Domains
0 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en
Text Length:198 chars
Detector Agreement:100%

Website Classification

Primary Category

documentation technical78% confidence
Type: static
Method: ml+structural

All Detected Categories

documentation technical
78%
government public service
42%
cryptocurrency blockchain
39%
technology software
34%
healthcare medical
30%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
264.29.17.195United States
AS16509Amazon.com, Inc.
21--

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T13B81B3377B69211AF333C89FA0C26B993010A121D1ABDAB9FF579F25D5CA1251E1278C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

48:TGR6Z9qGNGDY7nnr9YN6yhcCJd1XfBA3ILreuoi0Z1nde2ORegwDMWNW0eNMbQ/J:TGRe91n5O6Yp63XKk1Vr3hbQRkM

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:3849:BAAQQQSAIAAygGSABIQEEBBACgiAAIDAAAIUwAAAkgcCCEGAgECAEAAAEABKIAEggCDBoQOEcQwAEAAICFEA5AAJAAkACKwA

These hashes enable detection of similar websites and malware variants by comparing content similarity even when exact matches aren't found.

Image Hashes

Perceptual Hashes

Average Hash:ffffffcfc3c3ffff
Perceptual Hash:b199ce663199cc66
Difference Hash:000000181e040000
Wavelet Hash:3c3c3c00c0c0fcfc
Color Hash:#756ce0

Other Hashes

Crop Resistant:000000181e040000

Scan History

Scan history not available

Unable to load historical scan data