Security Scan Report: gillettepepsi.com

Redirected to:
https://www.gpcbeverage.com/
Site favicon
Submitted: Completed: publiccompleted
This website contacted 49 IPs in 2 countries across 24 domains to perform 123 HTTP transactions. The main domain is gillettepepsi.com and was registered 17 years ago.

Submitted URL: https://gillettepepsi.com

Effective URL:
https://www.gpcbeverage.com/
Redirected

AI Security Verdict

Safe Website

Confidence: 88%

1
Risk Score

Legitimate regional Pepsi distributor site; gillettepepsi.com simply redirects to the company's newer gpcbeverage.com domain. Search form only, no credential or payment collection, and no threat-intel or malware signals.

Safety Factors (5)
Self-branding: title/meta match the destination domain gpcbeverage.com
No credential or payment form anywhere on the page
No Indicators of Compromise, hunting-rule hits, Safe Browsing or IDS alerts
Third-party scripts are mainstream analytics/accessibility/CDN hosts ranked in the top 1M
Real business identifiers: named executives' customer testimonials, business hours, privacy policy, employee roles
Domain age information unavailable

Details

Page Title

GPC | Gillette Pepsi Companies | Beverage Distributors in La Crosse WI, Decorah IA, Rochester and Mankato MN

Scan Type

public

Domain Name Analysis

Within the commercial generic top-level domain (.com), 'gillettepepsi.com' is registered and has no subdomain. The core label 'gillettepepsi' covers 13 characters containing five vowels alongside 8 consonants. Splitting it apart reveals 2 words: gillette, pepsi. Median word length is 6.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://gillettepepsi.com

Page Load Overview

5.84s
Total Load Time
11.3 MB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:en
Text Length:7,428 chars
Detector Agreement:100%

Website Classification

Primary Category

education learning63% confidence
Type: spa
Method: ml+structural

All Detected Categories

education learning
63%
documentation technical
62%
government public service
57%
adult content
35%
technology software
31%

Detected Features

Search
OG: website

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2750.28.8.45United States
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2108.138.26.95Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
218.66.147.116Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
2142.251.110.95Google · CDNUnited States
AS15169Google LLC
279.127.211.89Datacamp · CDNFrankfurt am Main, Hesse, Germany
AS60068Datacamp Limited
292.123.104.141Akamai · CDNFrankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
215.197.193.217Aws · CLOUDSeattle, Washington, United States
AS16509Amazon.com, Inc.
254.242.142.108Aws · CLOUDAshburn, Virginia, United States
AS14618Amazon.com, Inc.
2157.240.0.6Facebook · CDNFrankfurt am Main, Hesse, Germany
AS32934Facebook, Inc.
12349--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T126B3D52259E53832006390E4B965B799BB83D30BC6574EC0F6FD43B68FC6DEA681394D

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:hauEiuhhsH47tNMEp9MMMxwqqSK3cmmTH:EThYFhK3cmIH

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:115343:IoSECq5AAGU9iHoQWCAQDiAJJQcQ6ADAIHIC0sgAECEQAAjC8AvQZBVXHk1LmGQEG0AQwlA4dkEIKRVZ4QTKexDwMJhMNBwB

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:00fffffffffffffe
Perceptual Hash:d56a556a552a572a
Difference Hash:9000000000000000
Wavelet Hash:00f2f0f002020202
Color Hash:#3a931f

Other Hashes

Crop Resistant:9000000000000000

Scan History

Scan history not available

Unable to load historical scan data