Security Scan Report: leibniz-ifl.de

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Submitted: Oct 8, 2025, 4:24:54 PMCompleted: Oct 8, 2025, 4:25:38 PMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 107 HTTP transactions. The main domain is leibniz-ifl.de and was registered NaN years ago.

Submitted URL: https://leibniz-ifl.de/

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

The site appears legitimate with no security concerns.

Safety Factors
Established research institute with public presence
Long‑standing domain registration (since 2020)
Clear institutional contact information
Standard search forms only
Domain age information unavailable

Details

Page Title

Willkommen am Leibniz-Institut für Länderkunde (IfL) – Leipzig

Scan Type

public

Language

🇩🇪

German

(80% confidence)

Category

social media network

(25%)

Domain Information

Domain 'leibniz-ifl.de' uses the German country-code top-level domain (.de). The core label 'leibniz-ifl' covers 11 characters with four vowels and 6 consonants; bonus characters include 1 hyphen. It segments into two words: leibniz, ifl. The median word length lands at 5 characters. 'ifl' is most common in English usage. Secondary signals appear in Malay and Chinese (Pinyin).

Screenshot

Security scan screenshot of https://leibniz-ifl.de/

Page Load Overview

19.34s
Total Load Time
107
HTTP Requests
1
Domains
1.5 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:5,788 chars
Detector Agreement:100%

Website Classification

Primary Category

social media network25% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

social media network
25%

Detected Features

Search

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
107185.243.133.230Germany
AS15817Mittwald CM Service GmbH & Co. KG
1071--

Detected Technologies9

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T18E04D62285F8343A01A243B2A6749F29BF16A663E5163D64F2BC038DDFD1F928D4375D

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:+/MznniMIXAFiwHXSM20HDYiGLgYq8dTMBg:+/MznniMIXAFiwHXSM20Hk

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:180924:B3RgQbUBW0FIGCEIABeiODLFRQASHECUnowDREFYgSrCOAHrMAtjoXFAgCghKEDAwIwFF8cgRwfgwIJrAbaCgHDKAAAtRDNE

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:ff8505070600ffff
Perceptual Hash:be3cc06e95d42e92
Difference Hash:20396d6c6d654580
Wavelet Hash:ff8105060600ffff
Color Hash:#1f2d93

Scan History

Scan history not available

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