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Security Scan Report: zennn-crash-inflash-3pcm0970pp.edgeone.app

Submitted: Feb 23, 2026, 6:27:48 PMCompleted: Feb 23, 2026, 6:29:20 PMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 2 HTTP transactions. The main domain is zennn-crash-inflash-3pcm0970pp.edgeone.app and was registered NaN years ago.

Submitted URL: https://zennn-crash-inflash-3pcm0970pp.edgeone.app/

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

AI Security Verdict

High Risk

Confidence: 85%

8
Risk Score

Site mimics WhatsApp on a newly created subdomain; likely phishing – do not provide any data.

Risk Factors
Brand impersonation (WhatsApp) on an unusual domain
New/unknown subdomain age
Low Cisco Umbrella ranking for a brand‑impersonating site
Hosted on a generic hosting platform subdomain (edgeone.app)
Suspicious OCR text suggesting phishing language
Domain age information unavailable

Details

Page Title

Zennn Crash Inflash - Bug WhatsApp Aris Store

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

technology software

(76%)

Domain Information

You're looking at domain 'zennn-crash-inflash-3pcm0970pp.edgeone.app' on the application-focused generic top-level domain (.app); it also runs on subdomain 'zennn-crash-inflash-3pcm0970pp'. The core label 'edgeone' covers 7 characters holding four vowels versus three consonants. Splitting it apart reveals 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://zennn-crash-inflash-3pcm0970pp.edgeone.app/

Page Load Overview

5.55s
Total Load Time
2
HTTP Requests
1
Domains
15 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
Text Length:2,093 chars
Detector Agreement:67%

Website Classification

Primary Category

technology software76% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
76%
social media network
73%
cryptocurrency blockchain
71%
documentation technical
64%
phishing scam
62%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
243.152.26.58Singapore
AS139341ACE
21--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1DC53A59661F734626953A1F56BA74B4736A09103D40ACD287FAC13848F8BFC8DDA3B4D

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:6JwGHF0FPFaFAb5QFIZ8o+FvFBFbrKdEWNOlgRgPVzzp:6J5mFAOb5QCCo+hvtrENPuz9

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:65884:QFQBFwAUABCV0AIZAsOCCkQxhRBw8MoR5NiRCVQCrAcASR0AhDQAOTHVOShEGkmKQmR7UgNJxoCgAiBIMAEBD6EBYAAEFTOI

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:001818191b1f1f1f
Perceptual Hash:8c4b237333793333
Difference Hash:f3b3b3b3b3b3b3f3
Wavelet Hash:1819191b1f1f1f1f
Color Hash:#d22d3d

Other Hashes

Crop Resistant:f3637363737373f3,f9f1f9f9f9f9f9f9

Scan History

Scan history not available

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