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Security Scan Report: julianucoutinho.pages.dev

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Submitted: Dec 11, 2025, 2:09:52 AMCompleted: Dec 11, 2025, 2:10:12 AMpubliccompleted
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Summary

This website contacted 55 IPs in 3 countries across 14 domains to perform 36 HTTP transactions. The main domain is julianucoutinho.pages.dev.

Submitted URL: https://julianucoutinho.pages.dev/zpnd-social-security-payment-schedule-2025-january-mgewq/

AI Security Verdict

High Risk

Confidence: 85%

8
Risk Score

Site impersonates Social Security information on an untrusted domain – treat as high‑risk phishing.

Risk Factors
Brand impersonation (Social Security) on a non‑official domain
Unranked, low‑reputation domain
Domain age unknown / likely newly registered
Domain age information unavailable

Details

Page Title

Social Security Payment Schedule 2025 January - Emilia Willis

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

government public service

(59%)

Domain Information

Domain 'julianucoutinho.pages.dev' uses the developer-focused generic top-level domain (.dev) and includes subdomain 'julianucoutinho'. The core label 'pages' covers 5 characters holding two vowels versus three consonants. Splitting it apart reveals 1 word: pages. The median word length lands at five characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://julianucoutinho.pages.dev/zpnd-social-security-payment-schedule-2025-january-mgewq/

Page Load Overview

3.01s
Total Load Time
36
HTTP Requests
14
Domains
837 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:3,100 chars
Detector Agreement:100%

Website Classification

Primary Category

government public service59% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

government public service
59%
adult content
41%
corporate
35%
healthcare medical
25%

Detected Features

Search
Articles
OG: website
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
36104.21.11.140United States
AS13335CLOUDFLARENET
0216.58.206.65United States
AS15169GOOGLE
0142.250.185.214United States
AS15169GOOGLE
0142.250.185.193United States
AS15169GOOGLE
0172.67.166.38United States
AS13335CLOUDFLARENET
0142.250.185.246United States
AS15169GOOGLE
0172.66.44.157United States
AS13335CLOUDFLARENET
0172.66.40.135United States
AS13335CLOUDFLARENET
0150.171.28.10United States
AS8075MICROSOFT-CORP-MSN-AS-BLOCK
0172.66.47.99United States
AS13335CLOUDFLARENET
3655--

Detected Technologies8

WordPressv6.4.3
100%
Open-Graph-Protocolvwebsite
100%
MetaGenerator
100%
JQueryv3.7.1
100%
Bootstrapv1.0.0
100%
HTTP/3
40%
Cloudflare Bot Management
40%
Cloudflare
40%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T168E2E73260AD10363E5F93ECC0A17318EEA9A615CA039F7A35FC32544F91EFA41A725D

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:NCHbZdapNLTWZsL//TkxFbqb3jiU7QjIZ0:yap5TWKL//uFbqb3jiU7QjIe

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:33962:ILECCBMSCASjhMeyIgyLRUUCgEHRyAEwLpYCEoAYQAVBjwopAwAEDDCEAATgAREeCiIpl87zMFUCJBBmaFAsRomJL0QRJ4OI

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:ff0038ffffc7c787
Perceptual Hash:b8c730e78df38c44
Difference Hash:0c4d732b3e3f1f3f
Wavelet Hash:e700b9fbcb838383
Color Hash:#9e87c5

Other Hashes

Crop Resistant:0c4d732b3e3f1f3f,48a8d8e4a4584848,1f380c64c6c6c653,08990b0e2c163667

Scan History

Scan history not available

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