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Security Scan Report: ecocosmeticcycle.pages.dev

Redirected to: https://ecocosmeticcycle.pages.dev/event-detail

Submitted: Jan 21, 2026, 5:46:03 AMCompleted: Jan 21, 2026, 5:47:10 AMpubliccompleted
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Summary

This website contacted 3 IPs in 1 country across 3 domains to perform 1 HTTP transaction. The main domain is ecocosmeticcycle.pages.dev and was registered NaN years ago.

Submitted URL: https://ecocosmeticcycle.pages.dev/event-detail.html

Effective URL: https://ecocosmeticcycle.pages.dev/event-detailRedirected

AI Security Verdict

High Risk

Confidence: 85%

7
Risk Score

Hidden password field indicates phishing; treat the site as high‑risk and do not provide login information.

Risk Factors
Hidden password field suggests credential harvesting
Login form on a site that appears informational only
Unranked domain increases suspicion
Domain age information unavailable

Details

Page Title

Limbah Kosmetik

Scan Type

public

Language

🇮🇩

ID

(50% confidence)

Category

education learning

(80%)

Domain Information

Within the developer-focused generic top-level domain (.dev), 'ecocosmeticcycle.pages.dev' is registered with subdomain 'ecocosmeticcycle'. The registrable portion 'pages' spans 5 characters split between 2 vowels and three consonants. Word splitting yields one word: pages. Median word length is 5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://ecocosmeticcycle.pages.dev/event-detail.html

Page Load Overview

0.99s
Total Load Time
19
HTTP Requests
3
Domains
891 KB
Total Size

Language Analysis

Primary Language

🇮🇩Indonesian
Code: id
Confidence:50%
Script:Unknown
Direction:ltr

Detection Details

Language Code:id
Detection Confidence:50%
Script Type:Unknown
HTML Lang Attribute:en
Text Length:1,594 chars
Detector Agreement:100%
Language mismatch: Declared as en but detected as id

Website Classification

Primary Category

education learning80% confidence
Type: webapp
Method: ml+structural

All Detected Categories

education learning
80%
documentation technical
64%
social_media
25%

Detected Features

Login Form

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
7142.250.184.234United States
AS15169
6142.251.140.163United States
AS15169GOOGLE
6172.66.44.84United States
AS13335CLOUDFLARENET
193--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1F552C62118F0243B026387CAEAF46B157DE5C107E64A6559B5FD0BE41FD6F4248A3B3C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:TcvcOL8ftvUjpuLgtKDzbAkmCZdSw7G8BDsqVM/rvcAAEbtalMgXl1tpVYlogwwN:o0OL8jowHNsd+lNXqqgEPW6LYbpF

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:14024:I3BQAAgMu5tAFsUJARB1BhDIUBIAlIDSCFkNLIFRHCwzImugZVGFYcGRAAacKCAIA4M4sgzGigfggEigGBc7kSwIlAhBqhwg

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:00010000ffffffff
Perceptual Hash:8a6ddd975678c0e0
Difference Hash:d555156569697169
Wavelet Hash:00010000bfffffff
Color Hash:#53ac5c

Other Hashes

Crop Resistant:d555156569697169,239c9876492957d5,65d5974d65656d45

Scan History

Scan history not available

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