Security Scan Report: guadalupemmclauring.pages.dev

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Submitted: May 13, 2026, 6:45:42 AMCompleted: May 13, 2026, 6:47:25 AMpubliccompleted
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Summary

This website contacted 11 IPs in 3 countries across 11 domains to perform 26 HTTP transactions. The main domain is guadalupemmclauring.pages.dev and was registered NaN years ago.

Submitted URL: https://guadalupemmclauring.pages.dev/sutdm-social-security-max-2025-benefits-increase-lnwww/

AI Security Verdict

Low Risk

Confidence: 78%

3
Risk Score

The site appears to be a low‑risk informational article; no phishing or malware indicators were found, though the unranked subdomain and heavy JS obfuscation suggest caution.

Risk Factors
Unranked domain (not in Cisco Umbrella top 1M)
High JavaScript obfuscation score (charcode manipulation, excessive concatenation)
Safety Factors
Page type is article (og:type=article) – informational content
No forms collecting credentials or payments
No malicious Indicators of Compromise or YARA matches
Domain age information unavailable

Details

Page Title

Social Security Max 2025 Benefits Increase - Guadalupe M McLaurin

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

healthcare medical

(61%)

Domain Information

The domain 'guadalupemmclauring.pages.dev' uses the developer-focused generic top-level domain (.dev) with subdomain 'guadalupemmclauring'. The second-level label 'pages' is 5 characters long split between two vowels and 3 consonants. Tokenizing the label suggests one word: pages. Median word length is 5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://guadalupemmclauring.pages.dev/sutdm-social-security-max-2025-benefits-increase-lnwww/

Page Load Overview

2.09s
Total Load Time
35
HTTP Requests
12
Domains
623 KB
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-US
Text Length:3,786 chars
Detector Agreement:100%

Website Classification

Primary Category

healthcare medical61% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

healthcare medical
61%
news/blog
35%
government public service
31%

Detected Features

Search
Articles
OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
5108.138.26.109United States
AS16509Amazon.com, Inc.
3167.114.50.130Montreal, Quebec, Canada
AS16276OVH SAS
352.5.159.58Ashburn, Virginia, United States
AS14618Amazon.com, Inc.
3172.67.75.176United States
AS13335Cloudflare, Inc.
3172.66.169.241United States
AS13335Cloudflare, Inc.
3150.171.28.10United States
AS8075Microsoft Corporation
3172.66.47.109United States
AS13335Cloudflare, Inc.
3172.67.71.34United States
AS13335Cloudflare, Inc.
3104.21.18.46United States
AS13335Cloudflare, Inc.
3176.9.114.118Falkenstein, Saxony, Germany
AS24940Hetzner Online GmbH
3511--

Detected Technologies10

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T107332962469C293A761E13DE95A4772CEABED530CB034AB575FD32188BC0DF202B715E

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:FapBT+uXwZp0SLNiI+rN2gQSbBmYrcyJqcFj:0XTBJqcFj

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:51521:hsDgGWwRZgDtGAIzAoQAWimiiIpMJ40GKI0gVAEoCHRUgRiQAskpkgCIyoEqgrYkhDGLMVMi8QyDQVPYUkwA2DEFRgQQgSRS

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:e7e7f989cbc3c3c3
Perceptual Hash:b9c633c431cc7b8c
Difference Hash:1e0e3b3b1a1b1b1b
Wavelet Hash:c7e7d98983c38383
Color Hash:#ac537e

Other Hashes

Crop Resistant:1e0e3b3b1a1b1b1b

Scan History

Scan history not available

Unable to load historical scan data