Security Scan Report: www.studentum.se

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Submitted: Jan 6, 2026, 8:19:38 AMCompleted: Jan 6, 2026, 8:21:18 AMpubliccompleted
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Summary

This website contacted 27 IPs in 5 countries across 19 domains to perform 68 HTTP transactions. The main domain is studentum.se and was registered NaN years ago.

Submitted URL: https://www.studentum.se/yrkesguiden/?utm_source=user.com&utm_medium=email&utm_campaign=nyhetsbrev-januari-2026&__ca__chat=11zjixs0difj

AI Security Verdict

High Risk

Confidence: 88%

8
Risk Score

Site impersonates Apple brand with many redirects; high‑risk phishing, should be avoided.

Risk Factors
Brand impersonation (Apple) on non‑official domain
Excessive redirects (7 redirects)
Unranked domain presenting a well‑known brand
Domain age information unavailable

Details

Page Title

Yrkesguiden

Scan Type

public

Language

🇸🇪

Swedish

(80% confidence)

Category

corporate

(70%)

Domain Information

The domain name 'www.studentum.se' uses the Swedish country-code top-level domain (.se) and includes subdomain 'www'. Its registrable label 'studentum' stretches across 9 characters containing 3 vowels alongside six consonants. Word splitting yields 2 words: student, um. Median word length comes out to 4.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://www.studentum.se/yrkesguiden/?utm_source=user.com&utm_medium=email&utm_campaign=nyhetsbrev-januari-2026&__ca__chat=11zjixs0difj

Page Load Overview

4.67s
Total Load Time
68
HTTP Requests
19
Domains
1.2 MB
Total Size

Language Analysis

Primary Language

🇸🇪Swedish
Code: sv
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

Language Code:sv
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:sv
Text Length:3,639 chars
Detector Agreement:100%

Website Classification

Primary Category

corporate70% confidence
Type: spa
Method: structural

All Detected Categories

corporate
70%
news/blog
40%
forum
40%

Detected Features

Search
OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
16172.64.147.188United States
AS13335CLOUDFLARENET
218.165.122.11United States
AS16509AMAZON-02
2104.16.78.6United States
AS13335CLOUDFLARENET
218.165.122.115United States
AS16509AMAZON-02
23.164.68.62United States
AS16509AMAZON-02
2216.239.32.36United States
AS15169GOOGLE
23.164.68.86United States
AS16509AMAZON-02
2216.58.210.142United States
AS15169GOOGLE
23.164.68.71United States
AS16509AMAZON-02
234.247.36.192Dublin, Leinster, Ireland
AS16509AMAZON-02
6827--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T16093C7639CF424365267A1A1BA79BB05EAA2C007D9479D40BDFC078C9FE2DB3496335C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:VAIjDhJlVendsNT3EJ2GjFDfLVAC3imOJmq6rHI25gqgNUbJJ+hSf0UlN2yC1b7D:rhJl8ndsAfLVBymOkqSHIiCUbJJ+FV

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:94563:MHQghSACAwCiHQJQc9COnGCRkOCGghCFYiTlTAClc1EEEMQESBMQGA4g0QDRwwVBBg4IFAhdkAGoSAhABAaAVDsUgPLkHTjB

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:ff3cffe7cf83c3c3
Perceptual Hash:b8c3e538c7249bac
Difference Hash:69791a0dbdbbb696
Wavelet Hash:bf0cc2c3c3c3c3c3
Color Hash:#2d8644

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data