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Security Scan Report: nataliejoalararua.pages.dev

Submitted: Nov 23, 2025, 7:01:25 PMCompleted: Nov 23, 2025, 7:03:31 PMpubliccompleted
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Summary

This website contacted 38 IPs in 4 countries across 14 domains to perform 34 HTTP transactions. The main domain is nataliejoalararua.pages.dev.

Submitted URL: https://nataliejoalararua.pages.dev/cuqij-social-security-payment-schedule-2025-pdf-form-cbiwm/

AI Security Verdict

High Risk

Confidence: 78%

8
Risk Score

Site impersonates Social Security on a new unranked domain; high‑risk phishing potential.

Risk Factors
Brand impersonation of U.S. Social Security on a non‑official domain
New/unranked domain lacking any established reputation
Potential social engineering to lure users into downloading or sharing personal information
Domain age information unavailable

Details

Page Title

Social Security Payment Schedule 2025 Pdf Form - Natalie J. OalaRarua

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

government public service

(40%)

Domain Information

Domain 'nataliejoalararua.pages.dev' uses the developer-focused generic top-level domain (.dev) with subdomain 'nataliejoalararua'. The second-level label 'pages' is 5 characters long containing 2 vowels alongside three consonants. Splitting it apart reveals one word: pages. Median word length comes out to five characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://nataliejoalararua.pages.dev/cuqij-social-security-payment-schedule-2025-pdf-form-cbiwm/

Page Load Overview

1.11s
Total Load Time
34
HTTP Requests
14
Domains
939 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:3,137 chars
Detector Agreement:100%

Website Classification

Primary Category

government public service40% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

government public service
40%
corporate
35%

Detected Features

Search
Articles
OG: website
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
34172.240.127.234United States
AS7979SERVERS-COM
17172.66.47.81United States
AS13335CLOUDFLARENET
2172.66.136.209United States
AS13335CLOUDFLARENET
2150.171.28.10United States
AS8075MICROSOFT-CORP-MSN-AS-BLOCK
2172.67.71.34United States
AS13335CLOUDFLARENET
2172.67.212.207United States
AS13335CLOUDFLARENET
1209.59.168.98United States
AS32244LIQUIDWEB
146.229.172.197Netherlands
AS39572DataWeb Global Group B.V.
1142.250.186.65United States
AS15169GOOGLE
1192.185.5.168United States
AS19871NETWORK-SOLUTIONS-HOSTING
3438--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T12903F83361F910323A9F83ECC1957328B9A8E215CA034B7671FC72A46F84CF605A760E

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:yhUZdapNXGCg4kYkxtSg4kYkKLXpUTrl5LGgkWZ5W1:japRTDpUTZ5LGgkWrW1

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:40452:2CTSFQMhA/RM5qhYdEmxDJABFIIqEAASgAhgCh8AsACIARTOkS9eUQJQSsPD+UBAQQJDSAGhCKBNhisCUhXomUjJscwyYFEg

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:8e00dbcbc7c3c7c3
Perceptual Hash:bc4b161618c9edbc
Difference Hash:301c2b333f2f0f2f
Wavelet Hash:8e00dbc3c7c3c7c3
Color Hash:#bf4062

Other Hashes

Crop Resistant:301c2b333f2f0f2f

Scan History

Scan history not available

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