Summary
This website contacted 1 IP in 1 country across 1 domain to perform 2 HTTP transactions. The main domain is nyhealthaccess.org and was registered NaN years ago.
Submitted URL: https://nyhealthaccess.org/news/100/
AI Security Verdict
Safe Website
Confidence: 92%
The site shows no malicious signals, is well‑established, and self‑brands correctly; it is classified as legitimate.
Safety Factors
Details
Page Title
HR1 -Changes Coming to NYS Medicaid under the "One Big Beautiful Bill" Law - CMS Issues Work Requirement Regulations June 1, 2026 - NY Health Access
Scan Type
public
Language
English
Category
social media network
(64%)Domain Information
Domain 'nyhealthaccess.org' uses the non-profit oriented generic top-level domain (.org) and has no subdomain. The core label 'nyhealthaccess' covers 14 characters split between 4 vowels and 10 consonants. Tokenizing the label suggests 3 words: ny, health, access. Median word length comes out to 6 characters. 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 |
|---|---|---|---|
| 117 | 64.176.223.68 | Piscataway, New Jersey, United States | AS20473The Constant Company, LLC |
| 117 | 1 | - | - |
Detected Technologies7
Content Similarity HashesFor malware variant detection
TLSH (Trend Micro Locality Sensitive Hash)
Specialized for malware detection and similarity analysis
ssdeep (Context Triggered Piecewise Hashing)
Detects 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