Security Scan Report: corpheanhugo-aefuv90cq7.edgeone.app

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Submitted: May 20, 2026, 9:23:06 PMCompleted: May 20, 2026, 9:24:27 PMpubliccompleted
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Summary

This website contacted 8 IPs in 2 countries across 8 domains to perform 13 HTTP transactions. The main domain is corpheanhugo-aefuv90cq7.edgeone.app and was registered NaN years ago.

Submitted URL: https://corpheanhugo-aefuv90cq7.edgeone.app/14824-visit-quad-cities-announces-2024-restaurant-week-dates-nominations-start-feb-1.html

The Cisco Umbrella rank of the primary domain is #455,732 of the top 1 million websites

AI Security Verdict

Low Risk

Confidence: 80%

2
Risk Score

The site appears to be a standard article page with no malicious indicators; low risk despite unknown subdomain age.

Risk Factors
Subdomain creation date unknown (potentially brand new)
Low Cisco Umbrella ranking (455,732) for the subdomain
Safety Factors
Page type is an article (og:type=article) with no brand impersonation
No forms or credential collection present
No network IDS alerts detected
No external malicious IoC links
No YARA malware matches
Domain age information unavailable

Details

Page Title

Visit Quad Cities announces 2024 Restaurant Week dates; nominations start Feb. 1

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

entertainment media

(53%)

Domain Information

The domain 'corpheanhugo-aefuv90cq7.edgeone.app' uses the application-focused generic top-level domain (.app) with subdomain 'corpheanhugo-aefuv90cq7'. The registrable portion 'edgeone' spans 7 characters split between 4 vowels and 3 consonants. Breaking it apart gives 2 words: edge, one. Average segment length settles at 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://corpheanhugo-aefuv90cq7.edgeone.app/14824-visit-quad-cities-announces-2024-restaurant-week-dates-nominations-start-feb-1.html

Page Load Overview

14.49s
Total Load Time
20
HTTP Requests
13
Domains
30 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-US
Text Length:1,091 chars
Detector Agreement:100%

Website Classification

Primary Category

entertainment media53% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

entertainment media
53%
adult content
43%
corporate
35%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
6172.240.108.84United States
AS7979Servers.com, Inc.
2192.178.183.95United States
AS15169Google LLC
2104.20.8.223United States
AS13335Cloudflare, Inc.
2104.18.11.207United States
AS13335Cloudflare, Inc.
2142.251.14.94United States
AS15169Google LLC
2104.21.0.120United States
AS13335Cloudflare, Inc.
243.152.26.58Singapore
2104.20.23.96United States
AS13335Cloudflare, Inc.
208--

Detected Technologies4

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T12B42E773ED83112C7B224199B8D1B3BCFC29E416F3828CE9F5ECA32547C66CB4466659

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:brgqMoshnYf8zX+mOTXc/3OCX0UOm9OwXmXDJKJEJ/cfOgayZX4LJKk2C5zYrWaX:bQPhnz+Tc3RinJU/6J6AYrWag4Aw

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:12697:osANAwIQDJobtEoHIQgAKQKrwDrGIRyeIipAAFBgEiAjUICRpCgkElxjEYMoyBocwCEEZ1iQCWaBGwIOIBgstmmVBgAwAFIM

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:00c3dfc3cfffffff
Perceptual Hash:f53846433343c7ce
Difference Hash:4d2e361e1e000002
Wavelet Hash:00c2c2c2cefefeb0
Color Hash:#862d83

Other Hashes

Crop Resistant:4d2e361e1e000002

Scan History

Scan history not available

Unable to load historical scan data