Security Scan Report: nadiapedersenm.pages.dev

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Submitted: Dec 29, 2025, 4:25:28 PMCompleted: Dec 29, 2025, 4:26:47 PMpubliccompleted
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Summary

This website contacted 22 IPs in 1 country across 18 domains to perform 32 HTTP transactions. The main domain is nadiapedersenm.pages.dev and was registered NaN years ago.

Submitted URL: https://nadiapedersenm.pages.dev/lgprc-social-security-payment-schedule-2025-january-2025-uvhyg/

AI Security Verdict

High Risk

Confidence: 92%

9
Risk Score

High‑risk phishing site impersonating Social Security; do not trust or provide personal data.

Risk Factors
Brand impersonation of Social Security Administration on an untrusted domain
Malicious external link to pages.dev (clearfake) detected
Domain not in Cisco Umbrella top 1M while claiming official government information
Domain age information unavailable

Details

Page Title

Social Security Payment Schedule 2025 January 2025 - Nadia M. Pedersen

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

entertainment media

(63%)

Domain Information

Domain 'nadiapedersenm.pages.dev' uses the developer-focused generic top-level domain (.dev) and includes subdomain 'nadiapedersenm'. Count 5 characters in 'pages' holding two vowels versus three consonants. Segmentation suggests 1 word: pages. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://nadiapedersenm.pages.dev/lgprc-social-security-payment-schedule-2025-january-2025-uvhyg/

Page Load Overview

3.30s
Total Load Time
38
HTTP Requests
18
Domains
1.6 MB
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:3,543 chars
Detector Agreement:100%

Website Classification

Primary Category

entertainment media63% confidence
Type: dynamic
Method: ml+structural+ocr_tiebreaker

All Detected Categories

entertainment media
63%
technology software
48%
corporate
35%
documentation technical
35%
government public service
34%

Detected Features

Articles
OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
17216.150.16.65United States
1104.20.23.96United States
AS13335CLOUDFLARENET
1172.66.169.241United States
AS13335CLOUDFLARENET
1172.240.127.244United States
AS7979SERVERS-COM
1172.66.40.135United States
AS13335CLOUDFLARENET
1150.171.27.10United States
1150.171.28.10United States
AS8075MICROSOFT-CORP-MSN-AS-BLOCK
1188.114.96.3United States
1172.66.43.121United StatesUnknown
1172.67.180.98United States
AS13335CLOUDFLARENET
3822--

Detected Technologies10

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T12213187350DC24337A5F93E8D4A2B71CEAA5E610CA035FA976FC61649F80EF641A311E

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:DU3YLHb2frzQZdapzmTIZqNnhYK5Fla2nWZwT+8BmSN1WYJLtu:hapSTIUP5FsoWZwK8B1N1WYJLtu

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:43374:QQABAcMIQCoUBCELLOgCInXUAgARmU2iS1LcxhQoRWAewqeE6mjRAJIiBACAQYuyQzoGagRizqAAK4vGEdBUSAhuBgDABETq

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:ff00ff878787c7ff
Perceptual Hash:b2cdcd32b4b0c8cd
Difference Hash:3245132c2d2d1f32
Wavelet Hash:df00cd8787878787
Color Hash:#2d3e86

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data