Security Scan Report: careofbeds.se

Redirected to:
https://careofbeds.se/search?q=&options%5Bprefix%5D=last
Site favicon
Submitted: Sep 27, 2026, 1:40:24 PMCompleted: Sep 27, 2026, 1:41:46 PMpubliccompleted

This website contacted 48 IPs in 4 countries across 32 domains to perform 605 HTTP transactions. The main domain is careofbeds.se and was registered 2 years 8 months ago.

Submitted URL: https://careofbeds.se

Effective URL:

https://careofbeds.se/search?q=&options%5Bprefix%5D=last
Redirected

AI Security Verdict

Safe Website

Confidence: 88%

0
Risk Score

Care of Beds is a self-branded Swedish bed retailer on a ~2.6-year-old domain with only search, cart, and newsletter forms. No impersonation, no credential/payment harvesting, and no threat-intel, YARA, or phishing signals.

Safety Factors (5)
Site's own brand (Care of Beds) matches its domain — not typosquatting or impersonation
Brand names in meta description (Hästens, Dux, Tempur, Jensen) are product brands it resells, not a claim to BE those brands
Multiple legitimate third-party integrations (Shopify, Klaviyo, Trustpilot) consistent with a real e-commerce store
Public contact email and phone number ([email protected], 070-594 36 00) and physical store references
No credential-harvesting or payment form present on the captured page
Domain age information unavailable

Details

Page Title

Sök

Scan Type

public

Domain Name Analysis

The domain 'careofbeds.se' uses the Swedish country-code top-level domain (.se) and has no subdomain. The core label 'careofbeds' covers 10 characters holding four vowels versus six consonants. Splitting it apart reveals three words: care, of, beds. Median word length comes out to four characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://careofbeds.se

Page Load Overview

8.54s
Total Load Time
7.4 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:sv
Text Length:3,316 chars
Detector Agreement:67%

Website Classification

Primary Category

social media network68% confidence
Type: spa
Method: ml+structural

All Detected Categories

social media network
68%
healthcare medical
55%
government public service
44%
blog personal website
42%
news media journalism
38%

Detected Features

Search
OG: website
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
4123.227.38.32Cloudflare · CDNOttawa, Ontario, Canada
AS13335Cloudflare, Inc.
1252.222.236.60Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
1223.227.39.200Cloudflare · CDNOttawa, Ontario, Canada
AS13335Cloudflare, Inc.
12146.75.122.133Fastly · CDNFrankfurt am Main, Hesse, Germany
AS54113Fastly, Inc.
1220.250.198.32Azure · CLOUDZurich, Zurich, Switzerland
AS8075Microsoft Corporation
1234.160.147.240Google · CDNKansas City, Missouri, United States
AS396982Google LLC
1223.227.39.20Cloudflare · CDNOttawa, Ontario, Canada
AS13335Cloudflare, Inc.
12104.26.1.145Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
12104.16.124.96Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
12150.171.110.53Azure · CLOUDUnited States
AS8075Microsoft Corporation
60548--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T16AB4E765E0A9283A019301D077AB7ACCB67D9507D3478C607AAD8B189FD1EF39A7311F

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:HC/0tCJrjkuQAMo2hZegQ90vbxgWeARzD4W3M1ivr9pbLio/vIvj:HC/slzD4Q9pbLio/vi

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:506613:lAghEQaRFx8gafAlhECSSOC4mpAACEHN1cEUReAoCCATJBGnQkEaIQREgYkpEAfAIBKFjMgHPCAxQSoNK08mCbLoRwySBFBA

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:ff001800ffff0f00
Perceptual Hash:9a40239766b9dcc7
Difference Hash:8fa9f131693c5ee1
Wavelet Hash:ff003801ffff0f00
Color Hash:#663a78

Scan History

Scan history not available

Unable to load historical scan data