ScanMalware.com

Security Scan Report: mayakgomes.pages.dev

Submitted: Dec 16, 2025, 7:02:10 PMCompleted: Dec 16, 2025, 7:02:36 PMpubliccompleted

Summary

This website contacted 60 IPs in 0 countries across 14 domains to perform 34 HTTP transactions. The main domain is mayakgomes.pages.dev and was registered 5 years ago.

Submitted URL: https://mayakgomes.pages.dev/ypuxyrr-social-security-administration-2025-raise-photos-mmojrut/

AI Security Verdict

High Risk

Confidence: 88%

7
Risk Score

Site impersonates the Social Security Administration and is likely a phishing page.

Risk Factors
Brand impersonation of a government agency on a non‑official domain
Unranked/low‑reputation domain presenting official‑looking content
Potential misinformation about benefit increases
Domain age information unavailable

Details

Page Title

Social Security Administration 2025 Raise - Bunnie Tabina

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

news/blog

(30%)

Domain Information

The domain name 'mayakgomes.pages.dev' uses the developer-focused generic top-level domain (.dev), featuring subdomain 'mayakgomes'. The registrable portion 'pages' spans 5 characters containing two vowels alongside three consonants. It segments into one word: pages. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of c.statcounter.com

Page Load Overview

9.83s
Total Load Time
34
HTTP Requests
14
Domains
864 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:3,385 chars
Detector Agreement:100%

Website Classification

Primary Category

news/blog30% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

news/blog
30%
government public service
27%

Detected Features

Articles
OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
34104.21.3.64UnknownUnknown
0172.67.166.38UnknownUnknown
0142.250.186.118UnknownUnknown
0188.114.96.3UnknownUnknown
0172.66.47.15UnknownUnknown
0150.171.27.10UnknownUnknown
03.160.150.112UnknownUnknown
034.195.60.139UnknownUnknown
0104.21.11.140UnknownUnknown
0188.114.97.3UnknownUnknown
3460--

Page Statistics

34
Requests
17
Unique Domains
1.2 MB
Total Size

Detected Technologies7

WordPressv6.7.1
100%
Open-Graph-Protocolvarticle
100%
MetaGenerator
100%
JQueryv3.7.1
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

T1BB031C2292DD19773E4F93DA94A1B31CEA7AD614C6034A6A72F8B028DF44DF6017315E

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:S0TM4dHZdapzgkST9ZZMYxrsg6N3d3sEpgqviyJ:S0TM4NapUT9jMYxrsg6NxdgqviyJ

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:39678:L3GOEigMPDSq6LODQr1IUYMZKlIi+QMA0R+IDMDAqGIuHL1ggUbCCBgSEigEo2a4gRgVAhogStliFC1SEDgiBQGnBoUKkQIi

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:9f81cfc7c7c7c7cf
Perceptual Hash:b87c7c3c8e969292
Difference Hash:361b191e0f0f2f1b
Wavelet Hash:9f81cdc3c3c383c3
Color Hash:#931f8f

Other Hashes

Crop Resistant:361b191e0f0f2f1b,0012a15959d12200

Scan History

Scan history not available

Unable to load historical scan data