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Security Scan Report: rebeccafhinesr.pages.dev

Submitted: Nov 14, 2025, 9:19:22 PMCompleted: Nov 14, 2025, 9:20:26 PMpubliccompleted
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Summary

This website contacted 38 IPs in 0 countries across 15 domains to perform 41 HTTP transactions. The main domain is rebeccafhinesr.pages.dev.

Submitted URL: https://rebeccafhinesr.pages.dev/sypqk-social-security-deposit-dates-2025-calendar-jbccu/

AI Security Verdict

High Risk

Confidence: 92%

8
Risk Score

High risk site impersonating Social Security; likely phishing or misinformation.

Risk Factors
Brand impersonation of Social Security on an unranked, newly registered domain
Domain age appears to be zero days (very new site)
Unranked domain (not in Cisco Umbrella top 1M) used to mimic official service
Misleading content about Social Security deposit dates
Domain age information unavailable

Details

Page Title

Social Security Deposit Dates 2025 Calendar - Rebecca F Hines

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

government public service

(55%)

Domain Information

The domain name 'rebeccafhinesr.pages.dev' uses the developer-focused generic top-level domain (.dev); it also runs on subdomain 'rebeccafhinesr'. The second-level label 'pages' is 5 characters long split between 2 vowels and 3 consonants. Breaking it apart gives one word: pages. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://rebeccafhinesr.pages.dev/sypqk-social-security-deposit-dates-2025-calendar-jbccu/

Page Load Overview

40.14s
Total Load Time
41
HTTP Requests
15
Domains
1.4 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:4,882 chars
Detector Agreement:100%

Website Classification

Primary Category

government public service55% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

government public service
55%
healthcare medical
54%
news media journalism
53%
adult content
43%
finance banking
39%

Detected Features

Search
Articles
OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
4150.171.27.10UnknownUnknown
1172.67.180.98UnknownUnknown
1172.66.44.99UnknownUnknown
1188.114.96.3UnknownUnknown
1142.250.181.234UnknownUnknown
1142.250.186.67UnknownUnknown
1172.66.136.209UnknownUnknown
1172.66.47.157UnknownUnknown
1160.153.0.38UnknownUnknown
1172.66.43.121UnknownUnknown
4138--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1AF43E621C8B82C73246EA394A171772E9D93A507C6031D6939FCB6409B87DAB44BF6CD

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:pmZdapN7X2/lT4Zi1XxINIcR5/2PZdxsBU92UmGDst9Id/R8fm:p2apYlT4s1Xxyh/0dx8UAHt9Id/+fm

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:59533:IGgEoglwFCOCQk/TFmp4JSa07EEUYpjoIc8gIBQgEdgU9AJoOLDQxAErR1gMQAgAuBRRDEIAAEAADEwT0AtGAAeMJylUsEoo

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:ff00000000ffffff
Perceptual Hash:b847b0c532cdd639
Difference Hash:d10571110f233a3f
Wavelet Hash:ff00000000ffffff
Color Hash:#501f93

Other Hashes

Crop Resistant:d10571110f233a3f,0100017171011101,d2da5a525ada52b5

Scan History

Scan history not available

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