Security Scan Report: www.uni-test-nine.vercel.app

Redirected to:
https://www.uni-test-nine.vercel.app/
Submitted: Jul 3, 2026, 12:45:37 AMCompleted: Jul 3, 2026, 12:49:59 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-test-nine.vercel.app and was registered NaN years ago.

Submitted URL: http://www.uni-test-nine.vercel.app/

Effective URL: https://www.uni-test-nine.vercel.app/Redirected

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

(79%)

Domain Information

Domain 'www.uni-test-nine.vercel.app' uses the application-focused generic top-level domain (.app); it also runs on subdomain 'www.uni-test-nine'. The second-level label 'vercel' is 6 characters long split between 2 vowels and 4 consonants. It segments into 2 words: ver, cel. The median word length lands at three characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of http://www.uni-test-nine.vercel.app/

Page Load Overview

3.00s
Total Load Time
3
HTTP Requests
1
Domains
N/A
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 technical79% confidence
Type: static
Method: ml+structural

All Detected Categories

documentation technical
79%
government public service
44%
cryptocurrency blockchain
38%
technology software
35%
real estate property
30%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
3216.198.79.3United States
AS16509Amazon.com, Inc.
31--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T15F81B3377B68211AF333C89FA0C26B993010A121D1ABDAB9FF579F15D5CA1251E0378C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

48:TGR6Z9qGNGDY7nnr9YN6yhcCJd1XfBA3ILreuoi0Z1nde2ORegwDMWNW0eNMV/Jv:TGRe91n5O6Yp63XKk1Vr3hVRkM

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:3849:BAAQQQSAIAAygGSARIwEEBBACgiAAIDAAAIUwAAAkgcCCEGAgECAEAAAEABKIAEggCDBoQOEcQwAEAAICFEA5AAJAIkQCKwA

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:00003000c3c3ffff
Color Hash:#783a53

Other Hashes

Crop Resistant:000000181e040000

Scan History

Scan history not available

Unable to load historical scan data