Summary
This website contacted 14 IPs in 3 countries across 15 domains to perform 67 HTTP transactions. The main domain is darrickhcargillt.pages.dev and was registered NaN years ago.
Submitted URL: https://darrickhcargillt.pages.dev/yubam-social-security-max-income-allowed-2025-married-qkukt/
AI Security Verdict
Safe Website
Confidence: 95%
Legitimate informational page with no apparent security concerns.
Safety Factors
Details
Page Title
Social Security Max Income Allowed 2025 Married - Darrick H Cargill
Scan Type
public
Language
English
Category
news/blog
(40%)Domain Information
Domain 'darrickhcargillt.pages.dev' uses the developer-focused generic top-level domain (.dev); it also runs on subdomain 'darrickhcargillt'. The core label 'pages' covers 5 characters split between 2 vowels and 3 consonants. Breaking it apart gives 1 word: pages. No strong language cues emerged from the frequency lists.
Screenshot
Page Load Overview
Language Analysis
Primary Language
Detection Details
Website Classification
Primary Category
All Detected Categories
Detected Features
Domain & IP Information
| Requests | IP Address | Location | AS Autonomous System |
|---|---|---|---|
| 5 | 188.114.96.3 | United States | AS13335CLOUDFLARENET |
| 4 | 104.21.18.46 | United States | AS13335CLOUDFLARENET |
| 4 | 192.0.73.2 | San Francisco, California, United States | AS2635AUTOMATTIC |
| 4 | 167.114.50.130 | Montreal, Quebec, Canada | AS16276OVH SAS |
| 4 | 136.243.106.228 | Falkenstein, Saxony, Germany | AS24940Hetzner Online GmbH |
| 4 | 150.171.28.10 | United States | AS8075MICROSOFT-CORP-MSN-AS-BLOCK |
| 4 | 108.138.26.38 | Unknown | |
| 4 | 104.198.108.103 | The Dalles, Oregon, United States | AS396982GOOGLE-CLOUD-PLATFORM |
| 4 | 104.196.233.173 | The Dalles, Oregon, United States | AS396982GOOGLE-CLOUD-PLATFORM |
| 4 | 18.66.147.32 | United States | AS16509AMAZON-02 |
| 57 | 14 | - | - |
Detected Technologies9
Content Similarity HashesFor malware variant detection
TLSH (Trend Micro Locality Sensitive Hash)
Security-focusedSpecialized for malware detection and similarity analysis
ssdeep (Context Triggered Piecewise Hashing)
Context-awareDetects similar content even with modifications
sdhash (Similarity Digest Hashing)
High-precisionHigh-precision similarity detection for forensic analysis
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
Other Hashes
Scan History
Scan history not available
Unable to load historical scan data