Security Scan Report: ringcatchblog-dpopx82nsygo.edgeone.app

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Submitted: Completed: publiccompleted

AI Security Verdict

Low Risk

Confidence: 70%

2
Risk Score

The page is an informational article with no malicious indicators; low risk.

Risk Factors (2)
Unranked domain (not in Cisco Umbrella top 1M)
Subdomain on a hosting platform with unknown age
Safety Factors (3)
No forms or fields that collect credentials
No malicious JavaScript behavior or network exfiltration
Content appears to be a standard informational article
Domain age information unavailable

Details

Page Title

Who Is the Adam Driver Look-Alike You Might Not Know?

Scan Type

public

Domain Name Analysis

The domain 'ringcatchblog-dpopx82nsygo.edgeone.app' uses the application-focused generic top-level domain (.app); it also runs on subdomain 'ringcatchblog-dpopx82nsygo'. Count 7 characters in 'edgeone' split between four vowels and 3 consonants. Segmentation suggests 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://ringcatchblog-dpopx82nsygo.edgeone.app/adam-driver-look-alike.html

Page Load Overview

1.70s
Total Load Time
1.1 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en-US
Text Length:4,408 chars
Detector Agreement:100%

Website Classification

Primary Category

education learning79% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

education learning
79%
entertainment media
76%
documentation technical
76%
adult content
70%
real estate property
69%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
3172.240.127.242United States
AS7979Servers.com, Inc.
3142.250.154.95United States
AS15169Google LLC
3109.234.161.222France
AS50474O2switch SAS
3172.67.150.240United States
AS13335Cloudflare, Inc.
343.152.26.58Singapore
155--

Detected Technologies3

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T142820827FA81422827314146A196B7ECBB6D8417D3528CF0B49DF32DA7C9BDB14B3694

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:hPWIhnYf8zX+g2hlAw8JuC4FIzGRjgN+czUgEReMorWag4MVxE:ZWIhnz+gBCC44Kkw4lEYrWag4Wm

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:17583:xaBnwkEg61VHEMCAXMKAbgFUGACQANYOaFEDgJIiEQAgMEINqsE0wDAIJaQGDPN0QFgDKAhokYZCTMyCTFMDhiDABbGEIdUC

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:ffffffc3c18181ff
Perceptual Hash:b9c69e39e13e8498
Difference Hash:22000e0f0b0b2b2f
Wavelet Hash:9effff8181818183
Color Hash:#a6c587

Scan History

Scan history not available

Unable to load historical scan data