Security Scan Report: couponsvibesitus-dpj3k52h9qwd.edgeone.app

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Submitted: Jun 29, 2026, 4:01:32 AMCompleted: Jun 29, 2026, 4:02:41 AMpubliccompleted
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Summary

This website contacted 9 IPs in 3 countries across 9 domains to perform 1 HTTP transaction. The main domain is couponsvibesitus-dpj3k52h9qwd.edgeone.app and was registered NaN years ago.

Submitted URL: https://couponsvibesitus-dpj3k52h9qwd.edgeone.app/acl-live-at-moody-center.html

AI Security Verdict

Low Risk

Confidence: 75%

2
Risk Score

The site shows no phishing, malware, or credential‑harvesting indicators and is classified as low risk.

Risk Factors
Domain is unranked in Cisco Umbrella
Sub‑domain creation date unknown (could be brand‑new)
Hosted on a generic PaaS sub‑domain (edgeone.app)
Safety Factors
No forms that collect credentials or payment data
No external malicious links or IoC‑matched resources
No malicious JavaScript behavior detected
Content appears to be informational health article
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

(79%)

Domain Information

You're looking at domain 'couponsvibesitus-dpj3k52h9qwd.edgeone.app' on the application-focused generic top-level domain (.app); it also runs on subdomain 'couponsvibesitus-dpj3k52h9qwd'. The second-level label 'edgeone' is 7 characters long split between four vowels and 3 consonants. It segments into 2 words: edge, one. Median word length comes out to 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://couponsvibesitus-dpj3k52h9qwd.edgeone.app/acl-live-at-moody-center.html

Page Load Overview

2.69s
Total Load Time
18
HTTP Requests
15
Domains
257 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:4,598 chars
Detector Agreement:60%

Website Classification

Primary Category

healthcare medical79% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

healthcare medical
79%
adult content
67%
government public service
63%
documentation technical
51%
entertainment media
47%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2142.251.20.95United States
AS15169Google LLC
2196.3.100.162Mozambique
AS31960Eduardo Mondlane University
2172.67.150.240United States
AS13335Cloudflare, Inc.
2196.3.101.3Mozambique
AS31960Eduardo Mondlane University
243.152.26.58Singapore
2172.240.108.84United States
AS7979Servers.com, Inc.
250.87.198.46Phoenix, Arizona, United States
AS46606Unified Layer
2104.18.33.206United States
AS13335Cloudflare, Inc.
2150.171.109.36United States
AS8075Microsoft Corporation
189--

Detected Technologies3

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T182822D37FA82011CB97341597142FBFCB919802AD7018CB6B4ACB3A8DFC6AD76462794

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:7zhnYf8zX+stI/vV4NvMcUtK6wmillZcGebBIoC6Uag49UVJ:7zhnz+stI/vV4NvMNtKHllmGIDC6Uag7

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:17874:YMGwvIwAgIGOJKFAcWQDQJwuG4guQOAIQEI8ggEALBgmhTscBAHYKFCAE9SwSBBSyVoAtNJCQMOC4HEZEQMDHGnShOLoAIA4

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:e787ffffc3838383
Perceptual Hash:bcc634e2e3c1c3c3
Difference Hash:0c2e600a1b373f3b
Wavelet Hash:e781ffff81818181
Color Hash:#79d292

Other Hashes

Crop Resistant:0c2e600a1b373f3b

Scan History

Scan history not available

Unable to load historical scan data