Security Scan Report: santander-remaster-whats-fb-kappa.vercel.app

Redirected to:
https://santander-remaster-whats-fb-kappa.vercel.app/
Submitted: Completed: publiccompleted
This website contacted 18 IPs in 2 countries across 10 domains to perform 24 HTTP transactions. The main domain is vercel.app and was registered 6 years ago.

Submitted URL: http://santander-remaster-whats-fb-kappa.vercel.app/

Effective URL:
https://santander-remaster-whats-fb-kappa.vercel.app/
Redirected

AI Security Verdict

High Risk

Confidence: 76%

8
Risk Score

Vercel subdomain impersonating Santander with a pre-approved personal-loan lure and a single-source phishing report; no form captured here, but treat as a bank-phishing funnel and avoid entering any data.

Risk Factors (4)
Brand impersonation of Santander on a non-official, random-looking vercel.app subdomain
Single-source phishing threat-intel match on the primary domain
Unranked domain (not in Cisco Umbrella top 1M) contradicted by the claim to be a major bank's loan portal
Exclusive/pre-approved loan bait typical of banking-phishing lures
Domain age information unavailable

Details

Page Title

Préstamo Personal Santander

Scan Type

public

Domain Name Analysis

Domain 'santander-remaster-whats-fb-kappa.vercel.app' uses the application-focused generic top-level domain (.app) with subdomain 'santander-remaster-whats-fb-kappa'. Its registrable label 'vercel' stretches across 6 characters split between two vowels and 4 consonants. Splitting it apart reveals two words: ver, cel. Median word length comes out to three characters. No strong language cues emerged from the frequency lists.

Screenshot

Q a Acceso ‘he OFERTA EXCLUSIVA Préstamo Personal Inmediato Préstamos personales para cubrir cualquier eventualidad. Apro! para clientes Santander Selecciona tu monto $250,000 —_——— Consultar...

Page Load Overview

10.46s
Total Load Time
771 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:es-MX
Text Length:652 chars
Detector Agreement:100%

Website Classification

Primary Category

finance banking54% confidence
Type: dynamic
Method: ml+structural+ocr_tiebreaker

All Detected Categories

finance banking
54%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
7216.198.79.3Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
1192.178.183.156Google · CDNUnited States
AS15169Google LLC
179.127.237.161Datacamp · CDNLondon, England, United Kingdom
AS60068Datacamp Limited
1104.17.24.14Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
1142.251.110.97Google · CDNUnited States
AS15169Google LLC
1216.239.34.36Google · CDNUnited States
AS15169Google LLC
1142.251.127.154Google · CDNUnited States
AS15169Google LLC
1142.251.14.94Google · CDNUnited States
AS15169Google LLC
1142.251.14.156Google · CDNUnited States
AS15169Google LLC
1142.251.110.132Google · CDNUnited States
AS15169Google LLC
2418--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1B682B66B69A30012B417D4A46FB29B5A6794D403E50BC9A83FDC2358CFC6DD6DC933AC

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:wslG+5lzk9p74jqSnlmQHFSTnQYfVGYhqcNYuFIfIsdbyaIs7byHi4BeYzBgrYVv:95lzk98LHG3ZFotzcMMIi6HVmIW/8m1

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:18617:AXlEJoBOWiR3YAMjUOxXwQhyFBA5ABkKtGLYVgH+6hgEAYAgEJIANAgIwsPgYSiEAYmAAhVhwQLzikQCl6RCLEEERKDMj4Ix

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:c3c3e7c7c7ffffff
Perceptual Hash:f76683c69bc98988
Difference Hash:8e8e0e0e0e0c0c1c
Wavelet Hash:c2c2c2c2c2e6e7e7
Color Hash:N/A

Scan History

Scan history not available

Unable to load historical scan data