Security Scan Report: au.dk

Redirected to: https://www.au.dk/

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Submitted: Jan 16, 2026, 1:15:33 PMCompleted: Jan 16, 2026, 1:17:04 PMpubliccompleted
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Summary

This website contacted 10 IPs in 3 countries across 11 domains to perform 75 HTTP transactions. The main domain is au.dk and was registered NaN years ago.

Submitted URL: https://au.dk

Effective URL: https://www.au.dk/Redirected

The Cisco Umbrella rank of the primary domain is #211,184 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 96%

0
Risk Score

Official Aarhus University site; no security concerns detected.

Safety Factors
Established domain with long registration history
Official university branding matches final URL
Standard cookie consent banner (non‑malicious)
No suspicious external links or redirects
Domain age information unavailable

Details

Page Title

Aarhus Universitet

Scan Type

public

Language

🇩🇰

Danish

(80% confidence)

Category

government public service

(49%)

Domain Information

Domain 'au.dk' uses the Danish country-code top-level domain (.dk) with no subdomain. The second-level label 'au' is 2 characters long with two vowels and 0 consonants. Breaking it apart gives one word: au. Median word length comes out to two characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://au.dk

Page Load Overview

2.91s
Total Load Time
68
HTTP Requests
12
Domains
4.2 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:53,469 chars
Detector Agreement:100%

Website Classification

Primary Category

government public service49% confidence
Type: static
Method: ml+structural

All Detected Categories

government public service
49%

Detected Features

Search

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
14209.38.34.181Germany
6104.16.175.226United States
AS13335CLOUDFLARENET
613.107.246.44United States
AS8075MICROSOFT-CORP-MSN-AS-BLOCK
6104.20.36.228United States
AS13335CLOUDFLARENET
6188.166.57.74United States
623.52.180.143Frankfurt am Main, Hesse, Germany
AS16625AKAMAI-AS
6108.138.7.97Unknown
613.107.213.44United States
AS8075MICROSOFT-CORP-MSN-AS-BLOCK
6142.250.185.168United States
AS15169GOOGLE
6185.45.20.48Aarhus, Central Jutland, Denmark
AS62138Aarhus Universitet
6810--

Detected Technologies6

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T11BB46431FAB5A135513D31A0F9208B56CA9BD31F4392B7FDB48C49350F49AD6AE2309E

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:9wjRpSlcbaT47II/U99Wq1GewiLgZM4FdRAycArNPAJcAaEtFIjR0/M+Vu2umgs+:p90q1GewiLgZM4FJPEt+jR0ngXiC4LdG

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:522847:IvICBqyRwAMBCWioqNIAtQCAlA9BCHU0YESgGagOgYSDILcAAHoiJqZgBEoREEGgtLAAkyGGIEfkASxYogEAAlDBRgKBGWAB

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:003c3c3c3c3c3c00
Perceptual Hash:cbf4340e31f91e98
Difference Hash:17e1696969696997
Wavelet Hash:80fcfc3c3c3cfd00
Color Hash:#7b79d2

Scan History

Scan history not available

Unable to load historical scan data