Security Scan Report: ariesddghugo-srhn0zpyem.edgeone.app

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Submitted: May 18, 2026, 6:02:28 PMCompleted: May 18, 2026, 6:03:51 PMpubliccompleted
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Summary

This website contacted 8 IPs in 2 countries across 8 domains to perform 15 HTTP transactions. The main domain is ariesddghugo-srhn0zpyem.edgeone.app and was registered NaN years ago.

Submitted URL: https://ariesddghugo-srhn0zpyem.edgeone.app/20643-11-caramel-frappe-mcdonalds-nutrition-facts.html

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

AI Security Verdict

Moderate Risk

Confidence: 78%

5
Risk Score

Moderate risk due to unknown subdomain age, low ranking, and high JS obfuscation, but no malicious indicators detected.

Risk Factors
Unknown subdomain age on a hosting platform
Low domain reputation rank
High JavaScript obfuscation (potentially suspicious code)
Brand mention on a non‑official domain
Safety Factors
No login or payment forms
No Indicators of Compromise matched
No JavaScript malware YARA patterns
No network IDS alerts
Page type is an article (informational)
Domain age information unavailable

Details

Page Title

11 Caramel Frappe Mcdonalds Nutrition Facts

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

news media journalism

(68%)

Domain Information

The domain 'ariesddghugo-srhn0zpyem.edgeone.app' uses the application-focused generic top-level domain (.app) with subdomain 'ariesddghugo-srhn0zpyem'. Its registrable label 'edgeone' stretches across 7 characters holding four vowels versus three 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://ariesddghugo-srhn0zpyem.edgeone.app/20643-11-caramel-frappe-mcdonalds-nutrition-facts.html

Page Load Overview

12.21s
Total Load Time
19
HTTP Requests
12
Domains
85 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:1,472 chars
Detector Agreement:100%

Website Classification

Primary Category

news media journalism68% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

news media journalism
68%
government public service
41%
healthcare medical
37%
corporate
35%
blog personal website
32%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
543.152.26.58Singapore
2172.240.127.243United States
AS7979Servers.com, Inc.
2172.66.169.241United States
AS13335Cloudflare, Inc.
2104.21.0.120United States
AS13335Cloudflare, Inc.
2104.20.7.223United States
AS13335Cloudflare, Inc.
2142.251.127.94United States
AS15169Google LLC
2142.251.13.95United States
AS15169Google LLC
2188.114.97.3United States
AS13335Cloudflare, Inc.
198--

Detected Technologies3

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T15932F737BB8110286BB253AD60D9F2BD38744026E7578CA914F6F33C878E7E74966B44

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:PL6KGIHk3VomvPYf85ZEQV+tJaKJKJX+MN0KmuXxLwhYYrWag4ofCvydAXq2:XkhnYf8zX+tlJKJXFiKmKUhYYrWag4Ma

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:11457:YOCMIIA5lo0IAksWhTACA5FMSSQlJiQlViJNIr9IhASQ4EaLHIEMHghQAAHB6VCBQLGgBogTAOHAEFGAcq0JAASGSYJhBoQ5

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:838f8183ffffffff
Perceptual Hash:bc3898c3e36165e5
Difference Hash:1b382f0fc0200030
Wavelet Hash:810f8100cfcfc3db
Color Hash:#1f4093

Other Hashes

Crop Resistant:1b382f0fc0200030

Scan History

Scan history not available

Unable to load historical scan data