Security Scan Report: skyredvnblog-dp6y1i29ga9d.edgeone.app

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Submitted: Jun 18, 2026, 4:05:47 AMCompleted: Jun 18, 2026, 4:07:03 AMpubliccompleted
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Summary

This website contacted 10 IPs in 4 countries across 10 domains to perform 2 HTTP transactions. The main domain is skyredvnblog-dp6y1i29ga9d.edgeone.app and was registered NaN years ago.

Submitted URL: https://skyredvnblog-dp6y1i29ga9d.edgeone.app/acl-live-at-moody-center.html

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

AI Security Verdict

Low Risk

Confidence: 72%

2
Risk Score

Low‑risk article page with no malicious indicators; safe for normal browsing.

Risk Factors
Subdomain on hosting platform with unknown creation date
Low Cisco Umbrella ranking (455,732)
Safety Factors
Page classified as an article/news content
No forms or data collection elements
JavaScript obfuscation consistent with normal minification
Domain age information unavailable

Details

Page Title

ACL Injuries: What to Expect at Moody Center’s Live Rehabilitation

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

healthcare medical

(80%)

Domain Information

You're looking at domain 'skyredvnblog-dp6y1i29ga9d.edgeone.app' on the application-focused generic top-level domain (.app); it also runs on subdomain 'skyredvnblog-dp6y1i29ga9d'. Its registrable label 'edgeone' stretches across 7 characters split between 4 vowels and three consonants. Word splitting yields two words: edge, one. Median word length is 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://skyredvnblog-dp6y1i29ga9d.edgeone.app/acl-live-at-moody-center.html

Page Load Overview

2.53s
Total Load Time
18
HTTP Requests
16
Domains
262 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:4,597 chars
Detector Agreement:60%

Website Classification

Primary Category

healthcare medical80% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

healthcare medical
80%
government public service
64%
adult content
64%
entertainment media
57%
documentation technical
51%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
9146.75.123.42Frankfurt am Main, Hesse, Germany
AS54113Fastly, Inc.
1172.67.150.240United States
AS13335Cloudflare, Inc.
1196.3.100.162Mozambique
AS31960Eduardo Mondlane University
1142.250.154.95United States
AS15169Google LLC
1172.240.108.76United States
AS7979Servers.com, Inc.
1196.3.101.3Mozambique
AS31960Eduardo Mondlane University
143.152.26.58Singapore
1150.171.109.194United States
AS8075Microsoft Corporation
150.87.198.46Phoenix, Arizona, United States
AS46606Unified Layer
1172.240.127.234United States
AS7979Servers.com, Inc.
1810--

Detected Technologies3

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1E3821C37FB91101CB57241597243FABCB51A842AD7118CB6747CB3A8CFC6ADB2463794

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:7zhnYf8zX+aB3WBlNBiGBfv6et66wmillZcGebBIoNjag4n+EkI:7zhnz+aRWLNcGpv6et6HllmGIDNjag4z

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:17920:AFogCgCcACkE0CNgaYRBgp6PNxoKuEzwEkAU5E8jKFA2QRAIEEXbQoMGBAEKSADwafAADBICgAE1ShUAKIFTCOIJiJIIgQCk

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:e783ffffc3838383
Perceptual Hash:bcc634e2e3c1c3c3
Difference Hash:0c2e600a1b373f3b
Wavelet Hash:e781ffff81818181
Color Hash:#ac7853

Other Hashes

Crop Resistant:0c2e600a1b373f3b

Scan History

Scan history not available

Unable to load historical scan data