Security Scan Report: mavquri-mpt-zelqano-k6x5pe94.pages.dev

Redirected to:
https://www.facebook.com/
Site favicon
Submitted: Completed: publiccompleted
This website contacted 7 IPs in 2 countries across 5 domains to perform 39 HTTP transactions. The main domain is pages.dev and was registered 6 years ago.

Submitted URL: https://mavquri-mpt-zelqano-k6x5pe94.pages.dev/

Effective URL:
https://www.facebook.com/
Redirected

AI Security Verdict

Confirmed Scam

Confidence: 96%

10
Risk Score

Confirmed Meta/Facebook 'Page Appeal' credential-phishing kit hosted on a disposable pages.dev subdomain, harvesting email+password while cloaking scanners by redirecting them to the real facebook.com. Do not enter credentials.

Risk Factors (5)
Known malicious phishing kit (Meta 'Page Appeal', family meta-page-appeal) byte/AST-identical to analyst-vetted samples
Brand impersonation of Meta/Facebook on a non-official, unranked pages.dev subdomain
Credential-harvesting login form (email + password) on a disposable hosting tenant
Scanner cloaking: datacenter IPs redirected to the genuine facebook.com while real victims see the lure
Entry host mavquri-mpt-zelqano-k6x5pe94.pages.dev has unknown creation date and no reputation
Domain age information unavailable

Details

Page Title

Meta for Business | Page Appeal

Scan Type

public

Domain Name Analysis

The domain 'mavquri-mpt-zelqano-k6x5pe94.pages.dev' uses the developer-focused generic top-level domain (.dev) and includes subdomain 'mavquri-mpt-zelqano-k6x5pe94'. The core label 'pages' covers 5 characters containing two vowels alongside three consonants. Splitting it apart reveals 1 word: pages. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://mavquri-mpt-zelqano-k6x5pe94.pages.dev/

Page Load Overview

0.33s
Total Load Time
2.4 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:78 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software67% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
67%
corporate business
45%
social media network
35%
documentation technical
28%
finance banking
28%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
9172.66.44.67Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
5157.240.0.35Facebook · CDNFrankfurt am Main, Hesse, Germany
AS32934Facebook, Inc.
5104.26.0.100Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
5157.240.0.6Facebook · CDNFrankfurt am Main, Hesse, Germany
AS32934Facebook, Inc.
5157.240.0.174Facebook · CDNFrankfurt am Main, Hesse, Germany
AS32934Facebook, Inc.
5172.66.47.189Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
5104.26.1.100Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
397--

Detected Technologies3

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T176019E13CC21D48DA270A3ABFD72B17CC989B90DAAA17C50B4D615DB4AE4BE0CC67952

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

12:hR0n56M8C2Zn816pX8VGuaXiKMci/CrC+fivVe1BtTG7faKj2a:hR056tC3spXoGa3WC+6vVqfC75j2a

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:707:AAAAAAAAAACAABAAAAgAAAAAAAABAACAAAABAAAIAAAgAQIAAAAAABAABAAABAAAAAAAgAAAAAAAAAAAAAAAAAAgAAAQAAAA

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:3fffffffffffffff
Perceptual Hash:870f0f0f0f0f0f0f
Difference Hash:c000000000000000
Wavelet Hash:30f0f0f000000000
Color Hash:#d0e06c

Other Hashes

Crop Resistant:c000000000000000

Scan History

Scan history not available

Unable to load historical scan data