Security Scan Report: www.somos-ecuador.vercel.app

Redirected to:
https://somos-ecuador.vercel.app/
Submitted: Completed: publiccompleted
This website contacted 7 IPs in 2 countries across 4 domains to perform 7 HTTP transactions. The main domain is vercel.app and was registered 6 years ago.

Submitted URL: https://www.somos-ecuador.vercel.app/

Effective URL:
https://somos-ecuador.vercel.app/
Redirected

AI Security Verdict

Confirmed Scam

Confidence: 95%

10
Risk Score

Fake Banco Pichincha loan page on a free .vercel.app subdomain that collects full name, national ID and phone number. Brand impersonation plus identity-data harvesting — do not enter data.

Risk Factors (5)
Brand impersonation of Banco Pichincha on a non-official .vercel.app subdomain
Collection of national ID (cédula) and phone number under a loan pretext
Fake pre-approval figures and loan terms used as a lure
Cross-origin IP-geolocation call from inline script
Free/instant hosting subdomain with unknown creation date
Domain age information unavailable

Details

Page Title

Crédito en Línea - Banco Pichincha

Scan Type

public

Domain Name Analysis

You're looking at domain 'www.somos-ecuador.vercel.app' on the application-focused generic top-level domain (.app) and includes subdomain 'www.somos-ecuador'. The core label 'vercel' covers 6 characters split between two vowels and four consonants. Tokenizing the label suggests two words: ver, cel. The median word length lands at 3 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://www.somos-ecuador.vercel.app/

Page Load Overview

7.32s
Total Load Time
1.1 MB
Total Size

Language Analysis

Primary Language

🇪🇸Spanish
Code: es
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:es
Text Length:892 chars
Detector Agreement:75%

Website Classification

Primary Category

finance banking59% confidence
Type: static
Method: ml+structural+ocr_tiebreaker

All Detected Categories

finance banking
59%
adult content
40%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
164.29.17.195Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
1216.198.79.131Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
1185.15.59.240United States
AS14907Wikimedia Foundation Inc.
1177.253.96.14Bogotá, Bogota D.C., Colombia
AS13489UNE EPM TELECOMUNICACIONES S.A.
1216.198.79.67Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
164.29.17.131Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
1216.198.79.195Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
77--

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T12A82B66956F30471ED93906937EB978A7154D003CD0ACE297FDE47808FCA994A9A3BCC

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:UrglY2Q3Pq4RS216S+8p/9GE6LXJIHtDghqYWHB1rYuzclN+IeKdgWx65/J5utAX:Urahq7HrKjt+I0qGN0GeYur8uBG

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:18413:DDYmICp7AISISUvFRZp5RA4EkBYkAICaCjkALAgFyphAFAMJpCF4AQUmsUgizkqIFECEZACCBRhszGJUtgBJFZOWQitE8okE

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:1818181818181818
Perceptual Hash:9933333333cccccc
Difference Hash:b2b2b2b2b2b2b2b2
Wavelet Hash:3c3c3c3c3c3c3c3c
Color Hash:#5140bf

Scan History

Scan history not available

Unable to load historical scan data