ScanMalware.com

Security Scan Report: couponsvibesitus-dpj3k52h9qwd.edgeone.app

Site favicon
Submitted: Jun 26, 2026, 9:07:53 AMCompleted: Jun 26, 2026, 9:09:03 AMpubliccompleted
Loading additional data...

Summary

This website contacted 5 IPs in 2 countries across 5 domains to perform 2 HTTP transactions. The main domain is couponsvibesitus-dpj3k52h9qwd.edgeone.app and was registered NaN years ago.

Submitted URL: https://couponsvibesitus-dpj3k52h9qwd.edgeone.app/andrew-wommack-on-youtube.html

AI Security Verdict

Moderate Risk

Confidence: 82%

4
Risk Score

The page is an article with heavily obfuscated JavaScript but lacks any credential collection or malware indicators, resulting in a moderate risk rating.

Risk Factors
High JavaScript obfuscation score
Unranked, unknown‑age subdomain
Hosting on a generic platform subdomain
Safety Factors
No forms collecting credentials or payment data
No malicious network activity or external C2 domains
Content type is an article (og:type=article) with no impersonation
Verdict cited a credential/login form, but DOM analysis found no password field (real or disguised) or payment field, and no other hard signal — credential-phishing framing unsupported; risk adjusted from 4 to 4
Domain age information unavailable

Details

Page Title

Andrew Wommack on YouTube: A Quick Guide for Worshipers and Learners

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

corporate

(35%)

Domain Information

The domain name 'couponsvibesitus-dpj3k52h9qwd.edgeone.app' uses the application-focused generic top-level domain (.app) and includes subdomain 'couponsvibesitus-dpj3k52h9qwd'. The core label 'edgeone' covers 7 characters holding four vowels versus three consonants. Word splitting yields two 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://couponsvibesitus-dpj3k52h9qwd.edgeone.app/andrew-wommack-on-youtube.html

Page Load Overview

2.62s
Total Load Time
14
HTTP Requests
10
Domains
108 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:4,753 chars
Detector Agreement:100%

Website Classification

Primary Category

corporate35% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

corporate
35%
education learning
27%
entertainment media
26%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
6172.217.208.95United States
AS15169Google LLC
2172.67.150.240United States
AS13335Cloudflare, Inc.
2101.33.10.10Frankfurt am Main, Hesse, Germany
AS139341ACE
23.171.214.88United States
AS16509Amazon.com, Inc.
2172.240.127.243United States
AS7979Servers.com, Inc.
145--

Detected Technologies2

Open-Graph-Protocolvarticle
100%
Statcounter
20%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T10572EA27AA80122C1AB24045A886B3FCF86D901AF7418DF5749DE33CA7C66DB8976754

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:7JhnYf8zX+ATQWnG11ywVshyEcorWag4MViU:7Jhnz+ATQW2jssEprWag4WL

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:17063:ABi4AIgGSgwB5QAIQRQKGZEOuZCEKGjAGQACEVRToAA2ITCUkQAFKg5IMQyQCylnAbkKSaEAgREQkoEQidR5AkohEAooBHIi

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:e787ffffc3838783
Perceptual Hash:bcc73620e3c3c3c3
Difference Hash:0e262006263b3a3f
Wavelet Hash:e782feff81818381
Color Hash:#c5bd87

Other Hashes

Crop Resistant:0e262006263b3a3f

Scan History

Scan history not available

Unable to load historical scan data