Security Scan Report: de-app-green-mobility.pages.dev

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Submitted: Dec 10, 2025, 1:49:17 AMCompleted: Dec 10, 2025, 1:49:44 AMpubliccompleted
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Summary

This website contacted 4 IPs in 1 country across 1 domain to perform 2 HTTP transactions. The main domain is de-app-green-mobility.pages.dev.

Submitted URL: https://de-app-green-mobility.pages.dev/

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

The site is a simple 404 page with no security concerns.

Safety Factors
No malicious Indicators of Compromise
No credential or payment collection
Content is a harmless error page
Domain age information unavailable

Details

Page Title

Planet 404

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

unknown

(0%)

Domain Information

You're looking at domain 'de-app-green-mobility.pages.dev' on the developer-focused generic top-level domain (.dev); it also runs on subdomain 'de-app-green-mobility'. Count 5 characters in 'pages' with 2 vowels and three consonants. Tokenizing the label suggests one word: pages. Median word length is five characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://de-app-green-mobility.pages.dev/

Page Load Overview

0.70s
Total Load Time
2
HTTP Requests
1
Domains
N/A
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:127 chars
Detector Agreement:100%

Website Classification

Primary Category

unknown0% confidence
Type: static
Method: structural

All Detected Categories

No categories detected

Detected Features

Search

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
0172.66.47.196United States
AS13335CLOUDFLARENET
0172.66.44.60United States
AS13335CLOUDFLARENET
02606:4700:310c::ac42:2c3cUnited States
AS13335CLOUDFLARENET
02606:4700:310c::ac42:2fc4United States
AS13335CLOUDFLARENET
24--

Detected Technologies3

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T16B81B752F5A30015780791281FEAA2483BA5D007DC4AD95C3FDEE2558FC9BFDD4A3388

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:n7Ql/aHKetnsJyTvdhQTPuqQpzb6VKqDaVuZRe6:7wSHKeaJOv7AmqQpzGgqDcuZRe6

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:4051:IAMUCAcUQACCAgBMAAGAIAVCAQZCAARAiAQQABAwIjEgRRAgAAEAABBAgASIEgCgSAgICAIASEAGAAAOKgAAFAMAmgICAEEC

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:000060e272600000
Perceptual Hash:e1a71e0ea4f0c34f
Difference Hash:2040c98ecec99040
Wavelet Hash:8060e3f7fe7f6010
Color Hash:#1f934e

Other Hashes

Crop Resistant:2040c98ecec99040

Scan History

Scan history not available

Unable to load historical scan data