ScanMalware.com

Security Scan Report: kanvasnetworkstudio-dpavr1iitykl.edgeone.app

Site favicon
Submitted: Jun 27, 2026, 4:17:27 AMCompleted: Jun 27, 2026, 4:18:34 AMpubliccompleted
Loading additional data...

Summary

This website contacted 8 IPs in 2 countries across 11 domains to perform 2 HTTP transactions. The main domain is kanvasnetworkstudio-dpavr1iitykl.edgeone.app and was registered NaN years ago.

Submitted URL: https://kanvasnetworkstudio-dpavr1iitykl.edgeone.app/

AI Security Verdict

Low Risk

Confidence: 80%

2
Risk Score

The site shows no credential or payment collection, no malicious indicators, and only low‑risk signals such as an unknown sub‑domain on a hosting platform.

Risk Factors
Unknown sub‑domain creation date
Unranked domain (not in Cisco Umbrella top 1 M)
Safety Factors
Absence of forms that collect credentials or payment data
No malicious external links or IoC hits
JavaScript obfuscation score likely due to minification, not malware
No network IDS alerts or YARA malware detections
Domain age information unavailable

Details

Page Title

portugal vs colombia 2026

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

entertainment media

(41%)

Domain Information

Domain 'kanvasnetworkstudio-dpavr1iitykl.edgeone.app' uses the application-focused generic top-level domain (.app), featuring subdomain 'kanvasnetworkstudio-dpavr1iitykl'. Its registrable label 'edgeone' stretches across 7 characters containing 4 vowels alongside three consonants. Word splitting yields two words: edge, one. The median word length lands at 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://kanvasnetworkstudio-dpavr1iitykl.edgeone.app/

Page Load Overview

1.48s
Total Load Time
27
HTTP Requests
16
Domains
489 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:1,267 chars
Detector Agreement:100%

Website Classification

Primary Category

entertainment media41% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

entertainment media
41%
corporate
25%

Detected Features

OG: website
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
643.152.26.58Singapore
AS139341ACE
3172.240.127.244United States
AS7979Servers.com, Inc.
3142.250.154.95United States
AS15169Google LLC
3150.171.27.10United States
AS8075Microsoft Corporation
3104.21.0.120United States
AS13335Cloudflare, Inc.
3104.18.10.207United States
AS13335Cloudflare, Inc.
3150.171.28.10United States
AS8075Microsoft Corporation
3150.171.27.11United States
AS8075Microsoft Corporation
278--

Detected Technologies4

Open-Graph-Protocolvwebsite
100%
Bootstrapv4.1.3
100%
WordPress
75%
Statcounter
20%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1C482F9279AC8943D665202CAE0D0B6FCA51E8C3BD762D8E9F4B7B7688FC49D74461210

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:PnxqBahnYf8zX+9xQkfGVUNsDea02FxGnbskQxHhjwK80Njag4n+Y8:PQahnz+9x/W9GnWNjag4+z

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:18495:EG73ZA0YQVbmBQECgYIGoEVLQjyUBIBC0EEAQRFEKgRDApRMjKxBaQNQgkIIQgQQKwYgACRZ1AhYboj6MIKo3AESDAMECSEJ

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:0000003c3c3c3c3c
Perceptual Hash:9a646c9bce3964cc
Difference Hash:3149977969797969
Wavelet Hash:3d01013d3d3d3d3d
Color Hash:#d2772d

Other Hashes

Crop Resistant:464680000000200e,a080903f3b82a0a0,cc8a2d0f2e6ec3c3,f8f8f0f0e0f8eb63,9a9a989edededede,3149977969797969

Scan History

Scan history not available

Unable to load historical scan data