Security Scan Report: solicita-ya.vercel.app

Submitted: Completed: publiccompleted
This website contacted 3 IPs in 2 countries across 3 domains to perform 6 HTTP transactions. The main domain is vercel.app and was registered 6 years ago.

Submitted URL: https://solicita-ya.vercel.app/

AI Security Verdict

Confirmed Scam

Confidence: 88%

9
Risk Score

Fake Banco Pichincha loan page on an unranked vercel.app subdomain that harvests name, national ID and phone; flagged by Google Safe Browsing for social engineering. Do not enter any data.

Risk Factors (6)
Impersonation of Banco Pichincha on a domain that is not the bank's official one
Google Safe Browsing Social Engineering detection
Harvesting of national ID and phone number via a deceptive 'credit pre-approval' flow
Free hosting-platform subdomain with unknown creation date and no domain reputation
Cross-origin IP lookup (api.ipify.org) indicating visitor fingerprinting
IDS alerts for actor-abused cloud hosting (vercel.app)
Domain age information unavailable

Details

Page Title

Crédito en Línea - Banco Pichincha

Scan Type

public

Domain Name Analysis

You're looking at domain 'solicita-ya.vercel.app' on the application-focused generic top-level domain (.app); it also runs on subdomain 'solicita-ya'. The core label 'vercel' covers 6 characters holding 2 vowels versus four consonants. Splitting it apart reveals 2 words: ver, cel. Median word length comes out to three characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://solicita-ya.vercel.app/

Page Load Overview

5.13s
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 banking37% confidence
Type: static
Method: ml+structural

All Detected Categories

finance banking
37%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
264.29.17.67Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
2185.15.59.240United States
AS14907Wikimedia Foundation Inc.
2177.253.96.14Bogotá, Bogota D.C., Colombia
AS13489UNE EPM TELECOMUNICACIONES S.A.
63--

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T15E82B76916F30471ED93906937DB978A7154D003DD0ACE297FDE47808FCA994A9A3BCC

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:grglY2Q3Pq4RS216S+8p/9GE6LXJIHtDghqYWHB1rYuzclN+IeKdgWx65/05utAX:grahq7HrK2t+I0qGN0GeYur8uBG

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:18428:Aii6JFoRgjkJ0EAhAEOUCD2kUgUCwQYQXHUXAEGiUlIkqROaEOgFQBwCwjEqWh+BIABCA3QUCKZQ9DGwKER+E6AxQgCCIREi

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:9933336633cccccc
Difference Hash:b2b2b2b2b2b2b2b2
Wavelet Hash:3c3c3c3c3c3c3c3c
Color Hash:#cad22d

Scan History

Scan history not available

Unable to load historical scan data