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Security Scan Report: jigglebabeblog-p5409zc5kc.edgeone.app

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Submitted: May 22, 2026, 2:26:03 PMCompleted: May 22, 2026, 2:27:23 PMpubliccompleted
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Summary

This website contacted 8 IPs in 2 countries across 8 domains to perform 11 HTTP transactions. The main domain is jigglebabeblog-p5409zc5kc.edgeone.app and was registered NaN years ago.

Submitted URL: https://jigglebabeblog-p5409zc5kc.edgeone.app/17254-20-vegetable-soup-nutrition-facts.html

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

AI Security Verdict

Low Risk

Confidence: 85%

2
Risk Score

Low risk site with no phishing, malware, or credential‑stealing indicators.

Risk Factors
High JavaScript obfuscation score (not a strong indicator alone)
Subdomain on a hosting platform with unknown creation date
Safety Factors
Absence of forms or credential collection
No malicious Indicators of Compromise
No JavaScript malware signatures
Content appears to be a benign article about vegetable soup
Domain age information unavailable

Details

Page Title

20 Vegetable Soup Nutrition Facts

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

healthcare medical

(88%)

Domain Information

Within the application-focused generic top-level domain (.app), 'jigglebabeblog-p5409zc5kc.edgeone.app' is registered and includes subdomain 'jigglebabeblog-p5409zc5kc'. The second-level label 'edgeone' is 7 characters long with four vowels and 3 consonants. Tokenizing the label suggests 2 words: edge, one. Average segment length settles at 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://jigglebabeblog-p5409zc5kc.edgeone.app/17254-20-vegetable-soup-nutrition-facts.html

Page Load Overview

11.90s
Total Load Time
18
HTTP Requests
13
Domains
33 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-US
Text Length:8,714 chars
Detector Agreement:100%

Website Classification

Primary Category

healthcare medical88% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

healthcare medical
88%
news media journalism
80%
government public service
65%
blog personal website
63%
adult content
56%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
4104.20.7.223United States
AS13335Cloudflare, Inc.
2172.66.169.241United States
AS13335Cloudflare, Inc.
2142.250.154.94United States
AS15169Google LLC
2192.178.183.95United States
AS15169Google LLC
2104.18.10.207United States
AS13335Cloudflare, Inc.
2172.240.127.234United States
AS7979Servers.com, Inc.
243.152.26.58Singapore
AS139341ACE
2172.67.150.240United States
AS13335Cloudflare, Inc.
188--

Detected Technologies4

Open-Graph-Protocolvarticle
100%
Bootstrapv4.1.3
100%
Statcounter
20%
DTScout
20%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T14292193BEB44312C57124254A2D373EC7939C016E79188F4A9A9933C07835CF5ABBEA3

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:brgqM9hnYf8zX+BDJ/csySjHAnEvCK6LMHMXuixusoSzYTdag4lDw:bQ9hnz+BDJUsySjHwTxu/IYTdag4xw

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:19741:QqJEBwmQEvYYLkJVi4MC98C9FNQDwMJuIdAfDJEIEoADgOBPgBjZcGEIiwEIDERMIUGgRJBQgITHiB46KCR8OFgE6hMTDeKB

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:c3dfc3c3c3c3c3c7
Perceptual Hash:b49b8b2c4f2cce64
Difference Hash:3b1e161616161616
Wavelet Hash:81cfc3c3c3c3c3c3
Color Hash:#862d7a

Other Hashes

Crop Resistant:3b1e161616161616

Scan History

Scan history not available

Unable to load historical scan data