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Security Scan Report: hurt-coffee-dcmfyukvvc-gld7d9abzv.edgeone.app

Submitted: Apr 25, 2026, 4:42:23 PMCompleted: Apr 25, 2026, 4:43:42 PMpubliccompleted
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Summary

This website contacted 2 IPs in 2 countries across 2 domains to perform 3 HTTP transactions. The main domain is hurt-coffee-dcmfyukvvc-gld7d9abzv.edgeone.app and was registered NaN years ago.

Submitted URL: https://hurt-coffee-dcmfyukvvc-gld7d9abzv.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: 72%

2
Risk Score

The site shows no malicious activity, but the subdomain is newly created on a hosting platform and has a low reputation ranking, resulting in a low risk rating.

Risk Factors
Unknown subdomain age on a hosting platform
Low domain ranking in Cisco Umbrella
Safety Factors
No forms, no password or payment fields
No malicious Indicators of Compromise
No JavaScript malware or credential exfiltration behavior
No external malicious links
Domain age information unavailable

Details

Page Title

JARVIS: Advanced Style Tutor

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

education learning

(90%)

Domain Information

Domain 'hurt-coffee-dcmfyukvvc-gld7d9abzv.edgeone.app' uses the application-focused generic top-level domain (.app) with subdomain 'hurt-coffee-dcmfyukvvc-gld7d9abzv'. Its registrable label 'edgeone' stretches across 7 characters split between 4 vowels and 3 consonants. Segmentation suggests 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://hurt-coffee-dcmfyukvvc-gld7d9abzv.edgeone.app/

Page Load Overview

0.84s
Total Load Time
3
HTTP Requests
2
Domains
7 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:414 chars
Detector Agreement:100%

Website Classification

Primary Category

education learning90% confidence
Type: static
Method: ml+structural

All Detected Categories

education learning
90%
documentation technical
45%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
243.152.26.58Singapore
AS139341ACE
1142.250.154.105United States
AS139341
32--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T148D1B522A0B6101208A3E07A7BF7578A2A72D407F74187A43DDD51D08FC76E98977DA9

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:3xRB38duCQXBvK0UJJXhWQ9BVPTGEfGjUrmuvlUgE:9Y3WQ9BvGjSNQ

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:6468:UbmKDJoABEQIBENA9SkJAMCAIggRIpBsATjAAAkBADEIg2XCEg8TJAMgUAwABopEBF6MB4JboAB0FxkkAQSQMAgGgKBSIgQR

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:1919193d3d010101
Perceptual Hash:8add20758add3077
Difference Hash:3131317161050101
Wavelet Hash:1d1d3d3d3f030303
Color Hash:#d2962d

Other Hashes

Crop Resistant:3131317161050101

Scan History

Scan history not available

Unable to load historical scan data