Security Scan Report: busy-green-dfsudpq4-dps6m1n1528d.edgeone.dev

Submitted: Sep 12, 2026, 4:51:51 PMCompleted: Sep 12, 2026, 4:54:02 PMpubliccompleted

AI Security Verdict

Low Risk

Confidence: 65%

2
Risk Score

Default Next.js starter template on a free EdgeOne subdomain. No forms, no credential/payment fields, no malware, no impersonation; the IP tag and IDS hits are reputation-only/informational.

Risk Factors (1)
Content served from a shared free-hosting subdomain (.edgeone.dev) whose own creation date is unknown; the apex registration date is not attributable to this page
Safety Factors (5)
No credential, login or payment forms on the page (verified DOM counts all zero)
No malware indicators from YARA, native YARA scanner, or kit roster
No brand impersonation: the Next.js/Vercel text is the default create-next-app template, not a page presenting itself as Vercel
No obfuscated JS, no credential exfiltration, no cross-origin form submission
Single-source reputation-only IP tag carries no content-malware weight
Domain age information unavailable

Details

Page Title

Next.js by Vercel - The React Frameworksecondary capture

Scan Type

public

Domain Name Analysis

Within the developer-focused generic top-level domain (.dev), 'busy-green-dfsudpq4-dps6m1n1528d.edgeone.dev' is registered; it also runs on subdomain 'busy-green-dfsudpq4-dps6m1n1528d'. The core label 'edgeone' covers 7 characters with four vowels and three consonants. Tokenizing the label suggests 2 words: edge, one. Median word length comes out to 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://busy-green-dfsudpq4-dps6m1n1528d.edgeone.dev/

Page Load Overview

35.21s
Total Load Time
N/A
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:en
Text Length:828 chars
Detector Agreement:67%

Website Classification

Primary Category

technology software71% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
71%
documentation technical
41%
adult content
36%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
143.174.247.29Singapore
043.174.246.29Singapore
12--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T150C1ED039CED8E197862A4C1C912F34DE54EA133D4244D5EF22CB4AA2F48DDA239F57E

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:S/mW7WJWAWZW5GzcMp3RFRiXcVvr9nqOfmgVTDZqZJ5ORg2r:SOW7WJWAWZW5GzcMp3RFRiXcVvr9nqOp

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:5946:GIAwDoMjACKSCBIIAIsAwIAEIDCIAgASEoCHACoXRMkaiCACAADAAlQCBASBBEkCCAMIOeKwgXAAYZ4EVwNlBAggAEAUQYBB

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:fcc381efe7ffffcf
Perceptual Hash:b368ccc393c86c3b
Difference Hash:41220b0c0a001416
Wavelet Hash:888081c3e7e7ffc2
Color Hash:#40a4bf

Other Hashes

Crop Resistant:41220b0c0a001416

Scan History

Scan history not available

Unable to load historical scan data