Security Scan Report: uni-ulm.de

Redirected to: https://www.uni-ulm.de/

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Submitted: Jan 7, 2026, 2:02:15 AMCompleted: Jan 7, 2026, 2:03:25 AMpubliccompleted
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Summary

This website contacted 2 IPs in 1 country across 3 domains to perform 67 HTTP transactions. The main domain is uni-ulm.de and was registered NaN years ago.

Submitted URL: https://uni-ulm.de

Effective URL: https://www.uni-ulm.de/Redirected

The Cisco Umbrella rank of the primary domain is #290,077 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

The site appears legitimate with no security concerns.

Safety Factors
Official university domain (uni-ulm.de)
Established domain age (> 600 days)
Content matches legitimate university privacy notice
Domain age information unavailable

Details

Page Title

Uni Ulm - Forschung, Studium, Wissenstransfer - Universität Ulm

Scan Type

public

Language

🇩🇪

German

(80% confidence)

Category

unknown

(0%)

Domain Information

Domain 'uni-ulm.de' uses the German country-code top-level domain (.de) with no subdomain. The second-level label 'uni-ulm' is 7 characters long holding three vowels versus 3 consonants, notching 1 hyphen. Splitting it apart reveals two words: uni, ulm. Expect three characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://uni-ulm.de

Page Load Overview

2.48s
Total Load Time
64
HTTP Requests
3
Domains
6.7 MB
Total Size

Language Analysis

Primary Language

🇩🇪German
Code: de
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

Language Code:de
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:de
Text Length:14,045 chars
Detector Agreement:100%

Website Classification

Primary Category

unknown0% confidence
Type: dynamic
Method: structural

All Detected Categories

No categories detected

Detected Features

Search

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
3289.107.186.29Germany
AS12843TelemaxX Telekommunikation GmbH
32134.60.1.22Ulm, Baden-Wurttemberg, Germany
AS553Universitaet Stuttgart
642--

Detected Technologies7

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1F2B393A0DAEC8D3A011343B76161BB08657F9E36D58229D1B2FF911D4FC1DC24BAF91A

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:JpnZDV0aWtcVgEVWbaYnqvia3Idy3g+PLywlcWne+Wne/sWveC8luvcrbIPmtCrF:wiqaiy3zPLsWRWmsWX8luvcrsZmgT

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:113581:BAJDGARkAwg0sohmxAQESAgxghaEEEHYylCwlIAgHQBmBIqQagAcoAJkEQRgkAKbBWQRI3NEAQgAhhIIaEWQbGQQbIxLQJAW

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:3c3c3c3c3c3c3c00
Perceptual Hash:cbdb348a21c9f46c
Difference Hash:696969e96969799f
Wavelet Hash:3d3c3c3c3c3d3d01
Color Hash:#2e862d

Scan History

Scan history not available

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