Security Scan Report: inappropriate-chocolate-fxt45mt7e2-r4e1jtywjl.edgeone.app

Submitted: Mar 22, 2026, 5:17:23 PMCompleted: Mar 22, 2026, 5:18:42 PMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 3 HTTP transactions. The main domain is inappropriate-chocolate-fxt45mt7e2-r4e1jtywjl.edgeone.app and was registered NaN years ago.

Submitted URL: https://inappropriate-chocolate-fxt45mt7e2-r4e1jtywjl.edgeone.app/

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

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

No suspicious activity detected; site appears legitimate.

Safety Factors
No credential or payment collection fields
Standard hosting platform with no malicious behavior
Low JavaScript obfuscation indicates no hidden malicious code
Page title and OCR text show generic file collection, no brand impersonation
Domain age information unavailable

Details

Page Title

Files Collection

Scan Type

public

Language

🇺🇸

English

(50% confidence)

Category

documentation technical

(41%)

Domain Information

Domain 'inappropriate-chocolate-fxt45mt7e2-r4e1jtywjl.edgeone.app' uses the application-focused generic top-level domain (.app), featuring subdomain 'inappropriate-chocolate-fxt45mt7e2-r4e1jtywjl'. Count 7 characters in 'edgeone' containing 4 vowels alongside 3 consonants. It segments into 2 words: edge, one. Median word length comes out to 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://inappropriate-chocolate-fxt45mt7e2-r4e1jtywjl.edgeone.app/

Page Load Overview

0.68s
Total Load Time
2
HTTP Requests
1
Domains
7 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:50%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:50%
Script Type:Latin
HTML Lang Attribute:zh
Text Length:132 chars
Detector Agreement:100%
Language mismatch: Declared as zh but detected as en

Website Classification

Primary Category

documentation technical41% confidence
Type: static
Method: ml+structural

All Detected Categories

documentation technical
41%
cryptocurrency blockchain
29%
healthcare medical
27%
news media journalism
25%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
243.152.26.58Singapore
21--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T14B32B6C9EFE30AC8642BC4685FFF67252229A053D44CC94CB5AE0E648F45188B4FB2B4

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:KrXrdEzawwpcoz5seK/ASMHmGgdkUfE0gB/hshchih1RaXQl:KrzhNK/lMHmGgdkqgCCkd

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:11482:IUWDV3RgBQNQNBQUAUWIkIACCIGMCQUIEXYLAABKiDBUAIkckoI0w4KAHSdnQMegATi8TSw0WEZaFgtAYAIGiDoAOiaGACEB

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:dcfcfcfce0808000
Perceptual Hash:da9a3c6d6c9a6161
Difference Hash:3030307000000000
Wavelet Hash:dcfcfcfcc0e0c0c0
Color Hash:#2dd259

Other Hashes

Crop Resistant:3030307000000000

Scan History

Scan history not available

Unable to load historical scan data