Security Scan Report: www.seoghoer.dk

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Submitted: Dec 10, 2025, 5:16:17 AMCompleted: Dec 10, 2025, 5:18:51 AMpubliccompleted
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Summary

This website contacted 104 IPs in 2 countries across 25 domains to perform 156 HTTP transactions. The main domain is seoghoer.dk and was registered NaN years ago.

Submitted URL: https://www.seoghoer.dk/kendte/skuespilleren-lorenzo-lamas-skal-skilles-sjette-gang

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

The site appears legitimate with no security concerns.

Safety Factors
Long‑standing domain registration
Absence of credential‑harvesting or payment forms
No known malicious Indicators of Compromise
Domain age information unavailable

Details

Page Title

Skuespilleren Lorenzo Lamas skal skilles for sjette gang | SE og HØR

Scan Type

public

Language

🇩🇰

Danish

(80% confidence)

Category

technology software

(57%)

Domain Information

The domain name 'www.seoghoer.dk' uses the Danish country-code top-level domain (.dk), featuring subdomain 'www'. Its registrable label 'seoghoer' stretches across 8 characters with 4 vowels and 4 consonants. Segmentation suggests four words: seo, g, hoe, r. Expect 2 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://www.seoghoer.dk/kendte/skuespilleren-lorenzo-lamas-skal-skilles-sjette-gang

Page Load Overview

20.97s
Total Load Time
156
HTTP Requests
25
Domains
1.9 MB
Total Size

Language Analysis

Primary Language

🇩🇰Danish
Code: da
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

Language Code:da
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:da
Text Length:94,292 chars
Detector Agreement:25%

Website Classification

Primary Category

technology software57% confidence
Type: webapp
Method: ml+structural

All Detected Categories

technology software
57%
news/blog
20%

Detected Features

OG: article

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
5323.56.205.206Frankfurt am Main, Hesse, Germany
AS16625AKAMAI-AS
118.245.46.121United States
AS16509AMAZON-02
118.66.147.104United States
AS16509AMAZON-02
1172.64.151.253United States
AS13335CLOUDFLARENET
1104.18.36.3United States
AS13335CLOUDFLARENET
1104.17.199.65United States
AS13335CLOUDFLARENET
1142.250.186.99United States
AS15169GOOGLE
12.20.142.121Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
118.66.147.118United States
AS16509AMAZON-02
1104.17.201.65United States
AS13335CLOUDFLARENET
156104--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T149B472307196351F0BA7C9F05282DB076AD2008A66825186C9D6CB3CBDD5D267DBF3AF

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

6144:3o5xqOh0tsfnQ0dKG8DlUFmxtq9nHU36JHXNFWR:3ojqOh0tsfnQ0dKG8DlUsxtqFHU3p

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:500115:TBF4hCCkHYAB8wwgkQACjAMgZZyJE0FDfWjGivSeMEAQ+UaIUKAAMgcKOkwYAGAoEkICUS0CkNki8EpBATYCguqRQgoDBBhH

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:00003c3c3c3c1800
Perceptual Hash:8b6631ce129ecb65
Difference Hash:4c46696969717096
Wavelet Hash:003c3c3c3c3c3c00
Color Hash:#ac5397

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data