Security Scan Report: acceptable-apricot-auhljcob-dpel8pu5qxnx.edgeone.app

Submitted: Jun 26, 2026, 10:04:26 PMCompleted: Jun 26, 2026, 10:05:33 PMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 4 HTTP transactions. The main domain is acceptable-apricot-auhljcob-dpel8pu5qxnx.edgeone.app and was registered NaN years ago.

Submitted URL: https://acceptable-apricot-auhljcob-dpel8pu5qxnx.edgeone.app/

AI Security Verdict

Low Risk

Confidence: 72%

3
Risk Score

Low risk site with no malicious indicators; likely a legitimate personal profile page.

Risk Factors
Domain is unranked in Cisco Umbrella
Subdomain on edgeone.app hosting platform with unknown creation date
Safety Factors
Absence of forms that collect credentials or payment data
No malicious JavaScript or external exfiltration observed
No external links to known malicious sites
Domain age information unavailable

Details

Page Title

Tushar Baroliya — Bioprocess Scientist

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

education learning

(47%)

Domain Information

The domain 'acceptable-apricot-auhljcob-dpel8pu5qxnx.edgeone.app' uses the application-focused generic top-level domain (.app) and includes subdomain 'acceptable-apricot-auhljcob-dpel8pu5qxnx'. The second-level label 'edgeone' is 7 characters long holding 4 vowels versus three consonants. Breaking it apart gives 2 words: edge, one. Expect 3.5 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://acceptable-apricot-auhljcob-dpel8pu5qxnx.edgeone.app/

Page Load Overview

1.31s
Total Load Time
8
HTTP Requests
3
Domains
214 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
Text Length:3,363 chars
Detector Agreement:100%

Website Classification

Primary Category

education learning47% confidence
Type: static
Method: ml+structural

All Detected Categories

education learning
47%
healthcare medical
27%
government public service
26%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
843.152.26.58Singapore
81--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T14DF3E06019F520162573E2C2B7831B8B52A48603C54AC425B7FE56C8CF8DEB4EB87F9D

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:t44xr015kd9Lc8Z2mWCwF+U2NiViTsbJcRDtkUaSXpuURjy:t44y09LcmwIU2EiwbiRzhy

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:170163:AKAKQFpIHgCgAA0IIxkmsDYrAQAIRDiyGWCCAW5peCGCAsBRAJAjUKJoYGBCBphIA2BaYEIIGBRSFoTwMDgkUARaFGI6CCRN

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:ffc7c7c3d3ffffff
Perceptual Hash:b1339ecccc933364
Difference Hash:00180c1c16000000
Wavelet Hash:fcdcc0c4033f0f0f
Color Hash:#87c5b5

Other Hashes

Crop Resistant:00180c1c16000000

Scan History

Scan history not available

Unable to load historical scan data