Security Scan Report: www.gencatportalverif.vercel.app

Redirected to:
https://gencatportalverif.vercel.app/
Submitted: Sep 15, 2026, 12:45:18 AMCompleted: Sep 15, 2026, 12:45:47 AMpubliccompleted

Summary

This website contacted 6 IPs in 3 countries across 4 domains to perform 2 HTTP transactions. The main domain is gencatportalverif.vercel.app and was registered 20 years ago.

Submitted URL: http://www.gencatportalverif.vercel.app/

Effective URL: https://gencatportalverif.vercel.app/Redirected

AI Security Verdict

Confirmed Scam

Confidence: 95%

10
Risk Score

Phishing page impersonating the Generalitat de Catalunya portal, harvesting email/password via a hidden login form that exfiltrates credentials to an external submit-form.com endpoint.

Risk Factors
Impersonation of Generalitat de Catalunya on a non-official domain
Password + email login form submitting to external submit-form.com
Credential exfiltration to third-party endpoint (IDS HIGH alert)
Free vercel.app subdomain with unknown creation date
Hidden form fields consistent with a phishing kit
No threat-intel or domain reputation (unranked in Cisco Umbrella)
Domain age information unavailable

Details

Page Title

Gencat Office Portal

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

technology software

(77%)

Domain Information

The domain 'www.gencatportalverif.vercel.app' uses the application-focused generic top-level domain (.app) and includes subdomain 'www.gencatportalverif'. The core label 'vercel' covers 6 characters split between two vowels and 4 consonants. Breaking it apart gives two words: ver, cel. Average segment length settles at three characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of http://www.gencatportalverif.vercel.app/

Page Load Overview

1.23s
Total Load Time
7
HTTP Requests
4
Domains
38 KB
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-US
Text Length:364 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software77% confidence
Type: webapp
Method: ml+structural

All Detected Categories

technology software
77%
documentation technical
42%
government public service
30%

Detected Features

Login Form

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
223.50.131.147Akamai · CDNFrankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
1216.198.79.131Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
164.29.17.67Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
1195.77.128.93Madrid, Madrid, Spain
AS210158Agencia Para La Adminitracion Digital De La Comunidad De Madrid
1216.198.79.67Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
123.50.131.133Akamai · CDNFrankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
76--

Page Statistics

7
Requests
4
Unique Domains
45.3 KB
Total Size

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T123D1306E28F6449755C779726EEFA6083D3480130808CE01FCAC55E55FE4D789EA6FB8

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:PyHi7YGbLtFyi9Utv8HIPgkgCcSy3tL5qiRnyncZ3TN1ih:aClt3dHIPxxc5NqCbVbih

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:6427:KgQxCCEQPjCjqBXpAgACAJEBARgsCUAFDBAKQMQACDKCCIXIIAKEGYIMIGAQAIBFAirWERIUjpQAMjhCIBzgRFEiggEAQAMi

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:0303030303030303
Perceptual Hash:a54a96b5a54a4bb5
Difference Hash:1717171716161616
Wavelet Hash:0707070707070707
Color Hash:#d279cb

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data