Security Scan Report: sp30ct-kalun-biz-vorex-zemik.pages.dev

Site favicon
Submitted: Completed: publiccompleted
This website contacted 3 IPs in 0 countries across 2 domains to perform 8 HTTP transactions. The main domain is pages.dev and was registered 6 years ago.

Submitted URL: https://sp30ct-kalun-biz-vorex-zemik.pages.dev/appeals/submit-appeal-form/return

AI Security Verdict

High Risk

Confidence: 80%

8
Risk Score

Fake Meta/Facebook 'Page Appeal' confirmation on an unrelated pages.dev subdomain. No form on this page itself, but the clone-of-Meta support flow is strong brand impersonation — do not enter account details anywhere in this flow.

Risk Factors (5)
Impersonation of Meta/Facebook branding on a non-Meta domain
Randomly named free-hosting subdomain (pages.dev) with unknown creation date
Fake official appeal/support confirmation page designed to make a phishing funnel appear legitimate
Coercive language pressuring the user not to share or question the reference code
No detectable legitimate corporate identity behind the hostname
Domain age information unavailable

Details

Page Title

Meta for Business | Page Appeal

Scan Type

public

Domain Name Analysis

Within the developer-focused generic top-level domain (.dev), 'sp30ct-kalun-biz-vorex-zemik.pages.dev' is registered; it also runs on subdomain 'sp30ct-kalun-biz-vorex-zemik'. The registrable portion 'pages' spans 5 characters with two vowels and three consonants. Word splitting yields one word: pages. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://sp30ct-kalun-biz-vorex-zemik.pages.dev/appeals/submit-appeal-form/return

Another page of the site in scan 8eb3601b

Page Load Overview

1.79s
Total Load Time
467 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:en
Text Length:1,361 chars
Detector Agreement:100%

Website Classification

Primary Category

social media network83% confidence
Type: static
Method: ml+structural

All Detected Categories

social media network
83%
technology software
64%
corporate business
36%
documentation technical
31%
e-commerce shopping
29%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
4188.114.97.3UnknownUnknown
2104.26.1.100UnknownUnknown
2188.114.96.3UnknownUnknown
83--

Detected Technologies4

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1EA02709ACEA0567BEED386DFB161BF6DB2CA149BC147A944B0F811C1C381F948D28536

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:gtkqRa+K0kKnh0hZwB4DuLBqiuzIal1juTdk:gtBNkSuZwVk

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:8421:AQUOIQPloC9EiwS2ogJREoMwiEaGpi8gQHpIXG0M7NoKIgTdmFmADIIJZJrIHDYhAZggcXQEkBJIXEIOyknPAAQJbEVIoCQW

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:ffe7e7e7efefc3e7
Perceptual Hash:b6069c999c669e39
Difference Hash:2a8e8ccc9cdc8e86
Wavelet Hash:ff42c2c2c6c6c2c7
Color Hash:#40acbf

Other Hashes

Crop Resistant:2a8e8ccc9cdc8e86

Scan History

Scan history not available

Unable to load historical scan data