Security Scan Report: app-ios.nursegrid.com

Submitted: Mar 4, 2026, 9:08:53 AMCompleted: Mar 4, 2026, 9:10:35 AMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 2 HTTP transactions. The main domain is app-ios.nursegrid.com and was registered NaN years ago.

Submitted URL: https://app-ios.nursegrid.com

The Cisco Umbrella rank of the primary domain is #122,119 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 99%

0
Risk Score

AI analysis skipped: HTTP 404 error page with no meaningful content to analyze.

Safety Factors
Error/status page with no actionable content
No forms, scripts, or interactive elements detected
Domain age information unavailable

Details

Page Title

N/A

Scan Type

public

Language

🇺🇸

English

(23% confidence)

Category

news media journalism

(39%)

Domain Information

Within the commercial generic top-level domain (.com), 'app-ios.nursegrid.com' is registered with subdomain 'app-ios'. Count 9 characters in 'nursegrid' with three vowels and 6 consonants. Tokenizing the label suggests 2 words: nurse, grid. Median word length is 4.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://app-ios.nursegrid.com

Page Load Overview

0.94s
Total Load Time
2
HTTP Requests
1
Domains
N/A
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:23%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:23%
Script Type:Latin
Text Length:122 chars
Detector Agreement:100%

Website Classification

Primary Category

news media journalism39% confidence
Type: static
Method: ml+structural

All Detected Categories

news media journalism
39%
government public service
36%
documentation technical
31%
adult content
30%
healthcare medical
28%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
252.202.54.162United States
21--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T17ED027774050053B5DB54EDC5D83E6058BD5F29A94310C447284D17855D5D45CC037C4

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

6:qzxV/5VHHQYk/B96zm7tLKa9VVWH1R8M1RGfZH5mNdxELa:kxV7Hfz+t9Vm6ZZm7xELa

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:1:0:bdf89d1b83a0e67a5cbcd7972c6ed203

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:00ffffffffffffff
Perceptual Hash:9b1b1b1b1b1b1b13
Difference Hash:9800000000000000
Wavelet Hash:00fff0f0f0f0f0f0
Color Hash:#87c5c5

Other Hashes

Crop Resistant:9800000000000000

Scan History

Scan history not available

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