Security Scan Report: ngobaka-dave64636.vercel.app

Redirected to:
https://ngobaka-dave64636.vercel.app/index1.html
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Submitted: Aug 20, 2026, 12:45:06 AMCompleted: Aug 20, 2026, 12:46:21 AMpubliccompleted

This website contacted 1 IP in 1 country across 6 domains to perform 16 HTTP transactions. The main domain is ngobaka-dave64636.vercel.app and was registered 6 years ago.

Submitted URL: https://ngobaka-dave64636.vercel.app/

Effective URL:

https://ngobaka-dave64636.vercel.app/index1.html
Redirected

AI Security Verdict

High Risk

Confidence: 88%

8
Risk Score

Page impersonates Meta/Facebook and harvests credentials via a login form; classify as high‑risk credential phishing.

Risk Factors (4)
Brand impersonation of Meta/Facebook on mismatched domain
Credential collection form
Unranked hosting subdomain with unknown age
Urgent verification demand typical of phishing
Domain age information unavailable

Details

Page Title

Meta für Unternehmen – Seitenattraktivität

Scan Type

public

Domain Name Analysis

The domain 'ngobaka-dave64636.vercel.app' uses the application-focused generic top-level domain (.app) with subdomain 'ngobaka-dave64636'. The registrable portion 'vercel' spans 6 characters with 2 vowels and four consonants. Segmentation suggests 2 words: ver, cel. Expect 3 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://ngobaka-dave64636.vercel.app/

Page Load Overview

1.05s
Total Load Time
9 KB
Total Size

Language Analysis

Primary Language

🇩🇪German
Code: de
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:de
Text Length:3,071 chars
Detector Agreement:75%

Website Classification

Primary Category

corporate business82% confidence
Type: webapp
Method: ml+structural

All Detected Categories

corporate business
82%

Detected Features

Login Form
Search
OG: article

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
1664.29.17.3United States
AS15169Google LLC
161--

Detected Technologies8

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T11AF25E11A9A5DC2A80CF59D86AB3612525F99307C2124A88FE7DABF10FAFC7CC777144

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:1acQ4eFIIACADGkJZUTiRgcGvsjTMe8GVu9pgUT7FDy:IFIZfJ6iiHl4u9pj7FDy

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:37130:TJo1ZIxILAQGWYgoRgGRh4AGGoDcDB8sOitggEEASg6GJC6ciIIR1cK8CqFCMEXAGAQWQKTUoIC0SsgYQAgADKIQAYwCIA0L

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:ffcfcf87c1cfcfff
Perceptual Hash:b933c45cc69cbc43
Difference Hash:18191b1b19b81818
Wavelet Hash:cf8580878087cfef
Color Hash:#77e06c

Scan History

Scan history not available

Unable to load historical scan data