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Security Scan Report: cestastiquinhositus-dp9g5yloanru.edgeone.app

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Submitted: Jun 17, 2026, 5:38:38 PMCompleted: Jun 17, 2026, 5:39:46 PMpubliccompleted
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Summary

This website contacted 5 IPs in 2 countries across 5 domains to perform 2 HTTP transactions. The main domain is cestastiquinhositus-dp9g5yloanru.edgeone.app and was registered NaN years ago.

Submitted URL: https://cestastiquinhositus-dp9g5yloanru.edgeone.app/33-cavendish-square-london-england-w1g-0pw.html

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

AI Security Verdict

Low Risk

Confidence: 78%

2
Risk Score

The site shows no phishing, malware, or credential‑harvesting behavior; it is low‑risk despite unknown sub‑domain age and low ranking.

Risk Factors
Sub‑domain creation date unknown (could be brand‑new)
Low Cisco Umbrella ranking (455,732) for a domain claiming no major brand
Safety Factors
No forms or fields that collect credentials
Content type is an article (og:type=article) about a location
No external malicious links or suspicious network activity
JavaScript obfuscation score high but attributed to normal minification
Domain age information unavailable

Details

Page Title

33 Cavendish Square, London: A Hub for Business and Innovation

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

corporate business

(91%)

Domain Information

You're looking at domain 'cestastiquinhositus-dp9g5yloanru.edgeone.app' on the application-focused generic top-level domain (.app), featuring subdomain 'cestastiquinhositus-dp9g5yloanru'. The registrable portion 'edgeone' spans 7 characters with four vowels and 3 consonants. It segments into 2 words: edge, one. Expect 3.5 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://cestastiquinhositus-dp9g5yloanru.edgeone.app/33-cavendish-square-london-england-w1g-0pw.html

Page Load Overview

1.64s
Total Load Time
14
HTTP Requests
11
Domains
130 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:4,197 chars
Detector Agreement:80%

Website Classification

Primary Category

corporate business91% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

corporate business
91%
real estate property
87%
blog personal website
83%
adult content
81%
phishing scam
80%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
6101.33.10.10Frankfurt am Main, Hesse, Germany
AS139341ACE
2172.240.108.68United States
AS7979Servers.com, Inc.
254.192.35.37United States
AS16509Amazon.com, Inc.
2172.217.208.95United States
AS15169Google LLC
2104.21.0.120United States
AS13335Cloudflare, 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

T1CE72E723AA80213C3662015AE5D1B7BCAE3C8917E3414DF4B9DDB32D9BCA7C7907965C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:KSshnYf8zX+w8V/4+6ECWQTs3jCDddZ9OEAbjXGGoC6Uag49UAq:Tshnz+w8V/4aCWQT+eDddzBAbj2jC6Ux

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:16454:UiCbQSUAwTAxiXFDyQADOgxblAgcIApLLDAVQqKgkgBNi5OA9p1EVlSBQAkAXzZUzRCABaOSwaRKMhMGCILBahKjgpIBT3QJ

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:197901013d617d7d
Perceptual Hash:8a3dcd889c3c3c3e
Difference Hash:f1d10d51c5d1c1c1
Wavelet Hash:197901017d657d7d
Color Hash:#d2799a

Other Hashes

Crop Resistant:f1d10d51c5d1c1c1

Scan History

Scan history not available

Unable to load historical scan data