ScanMalware.com

Security Scan Report: suterortwin.pages.dev

Submitted: Completed: publiccompleted

Summary

API
This view is built from:
Scan result: counts, verdicts, details, IPs, technologies, hashes/api/v1/result/27cb649f-feda-40d5-a7ad-14e96bc6a7c0Domain and IP registration (RDAP)/api/v1/rdap/27cb649f-feda-40d5-a7ad-14e96bc6a7c0How often this domain was scanned/api/v1/domain/stats/suterortwin.pages.devScan history for this domain/api/v1/domain/history/suterortwin.pages.dev?limit=15
This website contacted 12 IPs in 1 country across 13 domains to perform 33 HTTP transactions. The main domain is pages.dev and was registered 6 years ago.

Submitted URL: https://suterortwin.pages.dev/strvtd-social-security-calendar-2025-dates-rtwnzigk/

AI Security Verdict

High Risk

Confidence: 92%

8
Risk Score

High‑risk phishing site impersonating Social Security; malicious domain indicator present.

Risk Factors (4)
Primary domain malicious Indicators of Compromise
Brand impersonation of a government agency on an untrusted domain
Unranked domain in Cisco Umbrella
Potential social engineering to collect personal data
Domain age information unavailable

Details

Page Title

Social Security Calendar 2025 Dates - Suter Ortwin

Scan Type

public

Domain Name Analysis

You're looking at domain 'suterortwin.pages.dev' on the developer-focused generic top-level domain (.dev) with subdomain 'suterortwin'. The registrable portion 'pages' spans 5 characters split between 2 vowels and 3 consonants. Breaking it apart gives 1 word: pages. Average segment length settles at five characters. No strong language cues emerged from the frequency lists.

Screenshot

Suter Ortwin Home About Contact Disclaimer DMCA Privacy Policy Terms And Conditions Read Everything, Learn More Suter Ortwin. Social Security Calendar 2025 Dates Sociat Security Calendar 2025 Date...

Page Load Overview

112.38s
Total Load Time
1.5 MB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:en-US
Text Length:3,439 chars
Detector Agreement:100%

Website Classification

Primary Category

government public service56% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

government public service
56%
adult content
42%
corporate
35%
healthcare medical
31%
download file sharing
26%

Detected Features

Search
Articles
OG: website
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
16188.114.97.3United States
AS13335CLOUDFLARENET
3150.171.27.10UnknownUnknown
3142.251.208.3UnknownUnknown
2192.185.5.168UnknownUnknown
1104.20.23.96UnknownUnknown
1209.59.168.98UnknownUnknown
1142.250.184.202UnknownUnknown
113.77.182.13UnknownUnknown
1188.114.96.3United States
AS13335CLOUDFLARENET
1142.250.184.225UnknownUnknown
012--

Detected Technologies8

WordPressv6.4.3
100%
Open-Graph-Protocolvwebsite
100%
MetaGenerator
100%
JQueryv3.7.1
100%
Bootstrapv6.4.3
100%
PHP
50%
MySQL
50%
Statcounter
20%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1D043D721D6B82C67362E42A4A172733DAC1BA527D6021E7974FDB2142787CAF017F6CD

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:EWMjZdapNeai6DNB/3X3XMIaSj2vmSYTB73ilq0qcZPQYt:5oap0aTD5aSjVTB7ilq0hZIYt

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:57130:ZkABCoZxuVCIAiETAWkgCUAIAue+hQ8QAlzgJFAGhCqhZb1gBRSC4EsIAIaBsGYcBMFSAS1QCUiIQiQM4zJhECVKNsLT5BqC

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:fde7cf81838787df
Perceptual Hash:bac3c73549499696
Difference Hash:414d0d2b2b2e2f2f
Wavelet Hash:e1e7ed8183878387
Color Hash:N/A

Other Hashes

Crop Resistant:414d0d2b2b2e2f2f

Scan History

Scan history not available

Unable to load historical scan data