Security Scan Report: www.bodegaaurrera.com.mx

Redirected to: https://www.bodegaaurrera.com.mx/blocked?url=L2luaWNpbw==&uuid=84ef7064-2ce7-11f1-b8b3-d9215f9bb393&vid=&g=b

Submitted: Mar 31, 2026, 9:53:48 AMCompleted: Mar 31, 2026, 9:55:29 AMpubliccompleted
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Summary

This website contacted 12 IPs in 2 countries across 13 domains to perform 1 HTTP transaction. The main domain is bodegaaurrera.com.mx and was registered NaN years ago.

Submitted URL: https://www.bodegaaurrera.com.mx

Effective URL: https://www.bodegaaurrera.com.mx/blocked?url=L2luaWNpbw==&uuid=84ef7064-2ce7-11f1-b8b3-d9215f9bb393&vid=&g=bRedirected

The Cisco Umbrella rank of the primary domain is #114,396 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 94%

0
Risk Score

No suspicious activity detected; site appears legitimate.

Safety Factors
Well‑established domain age
Absence of credential or payment forms
No malicious Indicators of Compromise
No JavaScript malware detected
No IDS alerts detected
Domain age information unavailable

Details

Page Title

Verify Your Identity

Scan Type

public

Language

🇪🇸

Spanish

(80% confidence)

Category

documentation technical

(56%)

Domain Information

The domain name 'www.bodegaaurrera.com.mx' uses the Mexican country-code top-level domain (.com.mx), featuring subdomain 'www'. The second-level label 'bodegaaurrera' is 13 characters long containing 7 vowels alongside 6 consonants. Breaking it apart gives 4 words: bodega, aur, rer, a. Expect three characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://www.bodegaaurrera.com.mx

Page Load Overview

1.76s
Total Load Time
40
HTTP Requests
20
Domains
1.4 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

Language Code:es
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:es
Text Length:135 chars
Detector Agreement:67%

Website Classification

Primary Category

documentation technical56% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

documentation technical
56%
technology software
47%
adult content
36%
healthcare medical
33%
government public service
32%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
7142.251.141.74United States
AS15169Google LLC
363.140.62.200United States
AS16509Amazon.com, Inc.
352.208.15.121United States
323.52.182.209Frankfurt am Main, Hesse, Germany
AS16625Akamai Technologies, Inc.
334.120.250.63Kansas City, Missouri, United States
AS396982Google LLC
334.36.73.246Kansas City, Missouri, United States
AS396982Google LLC
3146.75.121.40Frankfurt am Main, Hesse, Germany
AS54113Fastly, Inc.
3104.17.64.242UnknownUnknown
3172.64.149.139United States
AS13335Cloudflare, Inc.
323.52.181.12Frankfurt am Main, Hesse, Germany
AS16625Akamai Technologies, Inc.
4012--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T127224DFB1905C074809342A671BF7B08707721CBFE95C854D4F95AB05759BEF4A42E6C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:OogCnrHrsr/+3ytbjpVhauUGz0bN+Aq4u9a9ma9ManPgvhiQyMjAOzHT9piu:JLmKw7N0+Aq11cPgvEQyMjrzz9pZ

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:10657:zESCwDyRcSBDRJCFIQCJIDgAqCB3INRoJYEA4wZA6PANQa4gnAY1wCBTFBcwG8Y4MGIQMwKAoAyGBoE5MGNAQokgTxMAYhN0

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:00ffe7ffffffffff
Perceptual Hash:f3735c4c4c4c3333
Difference Hash:00080c0c00000000
Wavelet Hash:00e7273f00000000
Color Hash:#ac539c

Other Hashes

Crop Resistant:00080c0c00000000

Scan History

Scan history not available

Unable to load historical scan data