Security Scan Report: shop-us.mercedesamgf1.com

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Submitted: Jul 19, 2026, 3:30:38 PMCompleted: Jul 19, 2026, 3:32:04 PMpubliccompleted
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Summary

This website contacted 9 IPs in 3 countries across 9 domains to perform 2 HTTP transactions. The main domain is shop-us.mercedesamgf1.com and was registered NaN years ago.

Submitted URL: https://shop-us.mercedesamgf1.com/collections/kimi-antonelli?srsltid=AfmBOorogd6zQOk0EHipH9CvZv3VWPH7DwtBb_kENclRh0gbxxDuGqT7

The Cisco Umbrella rank of the primary domain is #494,380 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 88%

2
Risk Score

The site appears to be a legitimate Mercedes‑AMG F1 merchandise store with no phishing or malware indicators.

Safety Factors
Brand alignment with domain
Long‑standing domain registration
Absence of malicious code or credential harvesting
No external threat intelligence hits
Domain age information unavailable

Details

Page Title

Kimi Antonelli

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

adult content

(83%)

Domain Information

You're looking at domain 'shop-us.mercedesamgf1.com' on the commercial generic top-level domain (.com) and includes subdomain 'shop-us'. The core label 'mercedesamgf1' covers 13 characters split between 4 vowels and 8 consonants, plus one digit. Tokenizing the label suggests 4 words: mercedes, am, gf, 1. Expect 2 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://shop-us.mercedesamgf1.com/collections/kimi-antonelli?srsltid=AfmBOorogd6zQOk0EHipH9CvZv3VWPH7DwtBb_kENclRh0gbxxDuGqT7

Page Load Overview

23.56s
Total Load Time
576
HTTP Requests
43
Domains
5.2 MB
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
Text Length:12,135 chars
Detector Agreement:100%

Website Classification

Primary Category

adult content83% confidence
Type: webapp
Method: ml+structural+ocr_tiebreaker

All Detected Categories

adult content
83%
e-commerce shopping
71%
government public service
62%
documentation technical
52%
corporate business
28%

Detected Features

Search
Products
OG: product.group

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
6423.227.39.20Ottawa, Ontario, Canada
AS13335Cloudflare, Inc.
64104.16.228.60Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
64104.18.36.90Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
6423.227.39.200Ottawa, Ontario, Canada
AS13335Cloudflare, Inc.
64172.64.144.86Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
6423.52.181.3Frankfurt am Main, Hesse, Germany
AS16625Akamai Technologies, Inc.
64172.66.149.193Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
6423.227.38.74Ottawa, Ontario, Canada
AS13335Cloudflare, Inc.
64146.75.122.133Fastly · CDNFrankfurt am Main, Hesse, Germany
AS54113Fastly, Inc.
5769--

Detected Technologies5

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T152B4F9A1E024483F8063D2E9FB113B5531AAE68BF34684D57EFD8768D7C6ED2631252C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

6144:n10OPPORvwORj+u44hzK86gwcU6e1GigE:10I/ORiu44hzKn1Gid

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:500045:cBLXJMEAUEs1MACpSiAIReiCiLgyIkQ8UgIBIAgzGMSCAwMDUWjlIIeEhLwOEyEHaAGK2rYsOskgplKCiSCWCiAwUpVApCj0

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:00000018fcfc9cbc
Perceptual Hash:d92136c88d366377
Difference Hash:523012b2b2316969
Wavelet Hash:00001818fffdbfbd
Color Hash:#6c3a78

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data