Security Scan Report: couponsvibesitus-dpj3k52h9qwd.edgeone.app

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Submitted: Jun 18, 2026, 12:34:22 PMCompleted: Jun 18, 2026, 12:35:31 PMpubliccompleted
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Summary

This website contacted 9 IPs in 4 countries across 9 domains to perform 2 HTTP transactions. The main domain is couponsvibesitus-dpj3k52h9qwd.edgeone.app and was registered NaN years ago.

Submitted URL: https://couponsvibesitus-dpj3k52h9qwd.edgeone.app/acl-tickets-austin-vip.html

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

AI Security Verdict

Low Risk

Confidence: 70%

2
Risk Score

Low‑risk page; no malicious indicators detected, likely a benign news article.

Risk Factors
Low domain ranking (455,732 in Cisco Umbrella)
Subdomain creation date unknown (potentially brand‑new)
Safety Factors
No credential or payment collection fields
No malicious JavaScript or network IDS alerts
Content classified as news media with high confidence
No external links to known malicious domains
Domain age information unavailable

Details

Page Title

Axessing Premium Experiences: Austin VIP Tickets and Event Insights

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

news media journalism

(89%)

Domain Information

Domain 'couponsvibesitus-dpj3k52h9qwd.edgeone.app' uses the application-focused generic top-level domain (.app); it also runs on subdomain 'couponsvibesitus-dpj3k52h9qwd'. Its registrable label 'edgeone' stretches across 7 characters containing four vowels alongside 3 consonants. Word splitting yields 2 words: edge, one. Median word length is 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://couponsvibesitus-dpj3k52h9qwd.edgeone.app/acl-tickets-austin-vip.html

Page Load Overview

1.78s
Total Load Time
17
HTTP Requests
14
Domains
361 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:10,097 chars
Detector Agreement:80%

Website Classification

Primary Category

news media journalism89% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

news media journalism
89%
entertainment media
80%
adult content
67%
government public service
66%
documentation technical
58%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
9172.240.127.244United States
AS7979Servers.com, Inc.
1172.217.208.95United States
AS15169Google LLC
1145.223.17.86Mumbai, Maharashtra, India
AS47583Hostinger International Limited
1142.250.154.119United States
AS15169Google LLC
143.152.26.58Singapore
1185.172.148.128Germany
AS44239proinity GmbH
1172.67.150.240United States
AS13335Cloudflare, Inc.
1146.75.120.159Frankfurt am Main, Hesse, Germany
AS54113Fastly, Inc.
13.161.76.68United States
AS16509Amazon.com, Inc.
179--

Detected Technologies3

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1D5A20A37FF402334ABB24296728DB7FC7B689819D7408991B06C7674A7846E749B27C8

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:7ZhnYf8zX+0RpEEtxLvviucjxttpkKNnQKhnBVS4oprgVYL05iLbB3PTTe0EPu/9:7Zhnz+09tQrFtt6KdQKhu4KaMoiLb5T9

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:23205:RkFqAIxoABEEavAAYUQBJUgOGYA+y0A4SAwqhsnSABCzARQJqhGLBhEEMSohWCKQAoWsYEkA0YQCkIMa0YAiKFAgASaIAkrQ

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:e787ffff83838383
Perceptual Hash:bc963621e3c3c3e1
Difference Hash:0c2c600227272727
Wavelet Hash:e782ffff81818181
Color Hash:#6c75e0

Other Hashes

Crop Resistant:0c2c600227272727

Scan History

Scan history not available

Unable to load historical scan data