ScanMalware.com

Security Scan Report: christophergemmac.pages.dev

Site favicon
Submitted: Dec 29, 2025, 12:53:03 AMCompleted: Dec 29, 2025, 12:54:16 AMpubliccompleted
Loading additional data...

Summary

This website contacted 10 IPs in 1 country across 14 domains to perform 32 HTTP transactions. The main domain is christophergemmac.pages.dev and was registered NaN years ago.

Submitted URL: https://christophergemmac.pages.dev/yjtqh-social-security-benefits-in-2025-payment-schedule-pdf-yqrlc/

AI Security Verdict

High Risk

Confidence: 88%

8
Risk Score

Site links to malicious domains and uses a social‑security scam lure; treat as high‑risk phishing.

Risk Factors
External links to known malicious domain pages.dev
Unranked domain with low reputation
Suspicious content offering Social Security Benefits PDF
Domain age information unavailable

Details

Page Title

Social Security Benefits In 2025 Payment Schedule Pdf - Christopher Gemma C

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

documentation technical

(63%)

Domain Information

You're looking at domain 'christophergemmac.pages.dev' on the developer-focused generic top-level domain (.dev) with subdomain 'christophergemmac'. Its registrable label 'pages' stretches across 5 characters containing two vowels alongside three consonants. Segmentation suggests 1 word: pages. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://christophergemmac.pages.dev/yjtqh-social-security-benefits-in-2025-payment-schedule-pdf-yqrlc/

Page Load Overview

5.74s
Total Load Time
32
HTTP Requests
0
Domains
N/A
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:2,303 chars
Detector Agreement:100%

Website Classification

Primary Category

documentation technical63% confidence
Type: dynamic
Method: ml+structural+ocr_tiebreaker

All Detected Categories

documentation technical
63%
adult content
39%
education learning
38%
government public service
37%
e-commerce shopping
33%

Detected Features

Search
Articles
OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
23188.114.96.3United States
AS13335CLOUDFLARENET
154.158.232.109UnknownUnknown
1104.20.23.96UnknownUnknown
1172.66.169.241United States
AS13335CLOUDFLARENET
1150.171.28.10UnknownUnknown
1209.59.168.98UnknownUnknown
1146.75.121.140UnknownUnknown
1104.26.15.73UnknownUnknown
1142.250.185.161UnknownUnknown
1104.21.11.140UnknownUnknown
010--

Detected Technologies8

WordPressv6.7.1
100%
Open-Graph-Protocolvarticle
100%
MetaGenerator
100%
JQueryv3.7.1
100%
PHP
50%
MySQL
50%
Statcounter
20%
Drupal
20%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T107231A3221EC047B3A9EA3ECD1A17B1DE96ADA30CA035AB9B2F974145F90DF2415711E

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:Nr3mNWQws9X4pZdapSTTQZ4PxAEEJ/OgioL7qRf8sHhofhvIIkv8sHCb8f28giRj:RRapCTQnEEJ/OgioLmh98sHCb8pRKJeh

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:45980:4UVEaygCxD0m4IEgKIIgIMINBgRiARHYAQBEMBPUEDmGAUJ6oBjiETFZlJEUMBIqSHChECMRgsKNCN5gAIo6CMABQVKAQUKk

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:00e7ff8787878787
Perceptual Hash:bec95966151c431f
Difference Hash:8c0f39272f0f3f1e
Wavelet Hash:00c3ff8787878787
Color Hash:#a987c5

Other Hashes

Crop Resistant:8c0f39272f0f3f1e,01014181a1814101,0001010101010100,243124861e73e74f

Scan History

Scan history not available

Unable to load historical scan data