Security Scan Report: aggressive-coffee-fnopt0wagc-004nitvez4.edgeone.app

Submitted: Feb 24, 2026, 12:50:29 AMCompleted: Feb 24, 2026, 12:51:42 AMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 1 HTTP transaction. The main domain is aggressive-coffee-fnopt0wagc-004nitvez4.edgeone.app and was registered NaN years ago.

Submitted URL: https://aggressive-coffee-fnopt0wagc-004nitvez4.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; the site appears legitimate.

Safety Factors
Hosted on a known free hosting platform (edgeone.app)
No credential or payment collection forms
No malicious Indicators of Compromise
No JavaScript malware detected
No network IDS alerts
Domain age information unavailable

Details

Page Title

Files Collection

Scan Type

public

Language

🇺🇸

English

(50% confidence)

Category

news media journalism

(29%)

Domain Information

Within the application-focused generic top-level domain (.app), 'aggressive-coffee-fnopt0wagc-004nitvez4.edgeone.app' is registered with subdomain 'aggressive-coffee-fnopt0wagc-004nitvez4'. The core label 'edgeone' covers 7 characters containing four vowels alongside 3 consonants. Breaking it apart gives 2 words: edge, one. Median word length is 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://aggressive-coffee-fnopt0wagc-004nitvez4.edgeone.app/

Page Load Overview

0.76s
Total Load Time
2
HTTP Requests
1
Domains
3 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:52 chars
Detector Agreement:100%
Language mismatch: Declared as zh but detected as en

Website Classification

Primary Category

news media journalism29% confidence
Type: static
Method: ml+structural

All Detected Categories

news media journalism
29%

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

T13102C6CAEBA306C9A82BC0682FFF5324222DE053C449CD5DB99E4F548F4518875EB3B4

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:KrXrdEzawwpcoz5seK/ASMHmGgdkUfE0gBzPh1RaXQl:KrzhNK/lMHmGgdkqgd

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:8703:YgUC1nQCDZMQPJUeAc2ElBCiSACEDSwCMlIJCgAKiDOwAIEMAMR2wwqACbcCANbQgTi9VQAmSERaBAhJABImKToCPWaWASGh

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:dcfcfcc0e0e0c0c0
Perceptual Hash:de9a9838686563c7
Difference Hash:3030200000000000
Wavelet Hash:dcfcfcf0f0e0c0c0
Color Hash:#b7c587

Other Hashes

Crop Resistant:3030200000000000

Scan History

Scan history not available

Unable to load historical scan data