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Security Scan Report: prior-fuchsia-a3c9i7btxm-lp0kk7n371.edgeone.app

Submitted: Mar 29, 2026, 3:43:10 AMCompleted: Mar 29, 2026, 3:44:42 AMpubliccompleted
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Summary

This website contacted 3 IPs in 3 countries across 3 domains to perform 4 HTTP transactions. The main domain is prior-fuchsia-a3c9i7btxm-lp0kk7n371.edgeone.app and was registered NaN years ago.

Submitted URL: https://prior-fuchsia-a3c9i7btxm-lp0kk7n371.edgeone.app/

The Cisco Umbrella rank of the primary domain is #455,732 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 92%

1
Risk Score

No suspicious activity detected; the site appears legitimate and safe.

Safety Factors
Hosted on a known free hosting platform (edgeone.app)
No credential or payment collection forms
No malicious Indicators of Compromise or YARA detections
No cross‑origin credential exfiltration
No brand impersonation or phishing language
Domain age information unavailable

Details

Page Title

For Kaur Ji 🥺

Scan Type

public

Language

🇪🇪

ET

(16% confidence)

Category

adult content

(62%)

Domain Information

The domain name 'prior-fuchsia-a3c9i7btxm-lp0kk7n371.edgeone.app' uses the application-focused generic top-level domain (.app); it also runs on subdomain 'prior-fuchsia-a3c9i7btxm-lp0kk7n371'. The second-level label 'edgeone' is 7 characters long holding 4 vowels versus three consonants. Tokenizing the label suggests 2 words: edge, one. The median word length lands at 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://prior-fuchsia-a3c9i7btxm-lp0kk7n371.edgeone.app/

Page Load Overview

1.63s
Total Load Time
4
HTTP Requests
3
Domains
236 KB
Total Size

Language Analysis

Primary Language

🇪🇪ET
Code: et
Confidence:16%
Script:Latin
Direction:ltr

Detection Details

Language Code:et
Detection Confidence:16%
Script Type:Latin
HTML Lang Attribute:en
Text Length:78 chars
Detector Agreement:50%
Language mismatch: Declared as en but detected as et

Website Classification

Primary Category

adult content62% confidence
Type: static
Method: ml+structural

All Detected Categories

adult content
62%
healthcare medical
55%
forum community discussion
53%
real estate property
53%
news media journalism
48%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2192.163.208.117United States
AS46606Unified Layer
1146.75.121.32Frankfurt am Main, Hesse, Germany
AS54113Fastly, Inc.
143.152.26.58Singapore
AS139341ACE
43--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T12141A017D65212053543E5A82EF29F494665980BC203C8FD3EED31A4CF8E7AA08F33AC

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

48:TCupStxS+MragTtb9vR5ZNafYnlVKeI5RJcpkhY:TCuMRMraGtJp5ZQfYnlUecRJJq

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:2070:AQAEQAAAAAAIAAEAQQAAQAEIQAAAAAoIAgABEgQAAQABCAAwIAAAAAEBBEQAYBAgAQAIEAICgAMBCIAAAAQAAAQCAIAIAIAA

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:ffffffe7e7ffffff
Perceptual Hash:b326cc993366cc99
Difference Hash:0000208c8c300000
Wavelet Hash:3c3c00e7e700fcfc
Color Hash:#3a7865

Other Hashes

Crop Resistant:0000208c8c300000

Scan History

Scan history not available

Unable to load historical scan data