Security Scan Report: appstart.ghost.io

Redirected to: https://tqg-rft-ewq-zhu-obj-rwf-win.netlify.app/

Submitted: Jan 2, 2026, 12:59:02 PMCompleted: Jan 2, 2026, 1:01:52 PMpubliccompleted
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Summary

This website contacted 3 IPs in 2 countries across 3 domains to perform 13 HTTP transactions. The main domain is tqg-rft-ewq-zhu-obj-rwf-win.netlify.app and was registered NaN years ago.

Submitted URL: https://appstart.ghost.io/suite/

Effective URL: https://tqg-rft-ewq-zhu-obj-rwf-win.netlify.app/Redirected

The Cisco Umbrella rank of the primary domain is #42,708 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Legitimate site with a simple verification step; no security concerns detected.

Safety Factors
Well‑established domain
No malicious Indicators of Compromise
No sensitive data collection
Standard human verification step only
Domain age information unavailable

Details

Page Title

Connect & Unlock

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

documentation technical

(50%)

Domain Information

Domain 'appstart.ghost.io' uses the British Indian Ocean Territory country-code top-level domain (.io); it also runs on subdomain 'appstart'. Its registrable label 'ghost' stretches across 5 characters containing one vowel alongside four consonants. Tokenizing the label suggests one word: ghost. Average segment length settles at five characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://appstart.ghost.io/suite/

Page Load Overview

93.52s
Total Load Time
18
HTTP Requests
3
Domains
105 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:476 chars
Detector Agreement:100%

Website Classification

Primary Category

documentation technical50% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

documentation technical
50%
cryptocurrency blockchain
40%
technology software
38%
adult content
33%
education learning
31%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
6146.75.123.7Frankfurt am Main, Hesse, Germany
AS54113FASTLY
635.157.26.135Frankfurt am Main, Hesse, Germany
AS16509AMAZON-02
6104.16.174.226United States
AS13335CLOUDFLARENET
183--

Detected Technologies1

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T19B32A558A8F81439820BC5EFBB794D0A3FC2E257DA2E005276BC57A44FE2CC1DA57844

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:4R5ZSPzelMnvrQUlMnvrakO+YZvT/PLb3nLbxTbQ:OlenkUenGvT/PLb3nLbxTbQ

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:11357:gMTbGDDYTKXBDMEDZgQHmNFAK0OgAIhoKJk4ISN2FEJE6WvEJIwR6GMAswCGIwAAExjXcCUY0AGIpRoisAlggSiAR0QAKjAj

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:0000084c3c180000
Perceptual Hash:93316cce3331ccce
Difference Hash:0000085a2a200000
Wavelet Hash:c0c0fcececd8f0f0
Color Hash:#53ac5c

Other Hashes

Crop Resistant:0000085a2a200000

Scan History

Scan history not available

Unable to load historical scan data