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Security Scan Report: grateful-coffee-mwjvsqd3o3-1adrb5gu30.edgeone.app

Submitted: Mar 24, 2026, 1:56:11 PMCompleted: Mar 24, 2026, 1:57:24 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 grateful-coffee-mwjvsqd3o3-1adrb5gu30.edgeone.app and was registered NaN years ago.

Submitted URL: https://grateful-coffee-mwjvsqd3o3-1adrb5gu30.edgeone.app/

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

AI Security Verdict

Low Risk

Confidence: 92%

2
Risk Score

No malicious activity detected; site appears to be a simple file collection on a hosting platform.

Risk Factors
Subdomain on hosting platform with unknown creation date (potentially newly created)
Low Cisco Umbrella ranking indicating limited reputation
Safety Factors
No forms, password, email, or payment fields present
No malicious JavaScript or YARA pattern matches
No cross‑origin credential exfiltration detected
No network IDS alerts
Domain age information unavailable

Details

Page Title

Files Collection

Scan Type

public

Language

🇺🇸

English

(72% confidence)

Category

documentation technical

(60%)

Domain Information

The domain name 'grateful-coffee-mwjvsqd3o3-1adrb5gu30.edgeone.app' uses the application-focused generic top-level domain (.app) with subdomain 'grateful-coffee-mwjvsqd3o3-1adrb5gu30'. The core label 'edgeone' covers 7 characters with four vowels and three consonants. Word splitting yields two 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://grateful-coffee-mwjvsqd3o3-1adrb5gu30.edgeone.app/

Page Load Overview

0.35s
Total Load Time
2
HTTP Requests
1
Domains
3 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:72%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:72%
Script Type:Latin
HTML Lang Attribute:zh
Text Length:92 chars
Detector Agreement:100%
Language mismatch: Declared as zh but detected as en

Website Classification

Primary Category

documentation technical60% confidence
Type: static
Method: ml+structural

All Detected Categories

documentation technical
60%
healthcare medical
39%
government public service
38%

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

T19612D7CAEBE706C9A81BC4682FFF5725222DE053C449C95CB99E0F548F0518875FB2B8

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:KrXrdEzawwpcoz5seK/ASMHmGgdkUfE0gBJCh4nRh1RaXQl:KrzhNK/lMHmGgdkqnYd

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:9652:cI0C1nICDQMQNJ0UJUWQjIMiCACEDQYAMFIJAwkKiDAQAJEIhcQ2zwCcDacCIMaEgXicdQguyuFaBQhFABIGCCoCOS6GABEH

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:dcfcfcf0e0e0c0c0
Perceptual Hash:da9a986c6c65c3c3
Difference Hash:3030700000000000
Wavelet Hash:dcfcfce0f0e0e0c0
Color Hash:#e0dc6c

Other Hashes

Crop Resistant:3030700000000000

Scan History

Scan history not available

Unable to load historical scan data