Security Scan Report: skimbeq.se

Submitted: Sep 25, 2026, 5:30:09 PMCompleted: Sep 25, 2026, 5:30:42 PMpubliccompleted

AI Security Verdict

Moderate Risk

Confidence: 50%

4
Risk Score

Brand-new, self-branded 'coming soon' page for a ski/MTB shop. No forms, no impersonation, no malware or threat-intel hits; risk stems only from the domain being ≤1 day old.

Risk Factors
Domain is ≤1 day old, so there is no track record for the site or the shop it intends to become
Safety Factors
Site displays its own brand (skimbeq.se) — no impersonation of another company
Zero forms; no password, payment, or credential fields of any kind
No Indicators of Compromise matches against the page or its resources
No JavaScript malware patterns, no network IDS alerts, no credential exfiltration
Static placeholder content with no user-interaction surface
Domain age information unavailable

Details

Page Title

SKIMBEQ – Ski and mountain bike equipment

Scan Type

public

Domain Name Analysis

The domain name 'skimbeq.se' uses the Swedish country-code top-level domain (.se) without a subdomain. The core label 'skimbeq' covers 7 characters containing 2 vowels alongside 5 consonants. Tokenizing the label suggests three words: skim, be, q. Average segment length settles at 2 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://skimbeq.se

Page Load Overview

1.09s
Total Load Time
156 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:33%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:sv-SE
Text Length:139 chars
Detector Agreement:33%
Language mismatch: Declared as sv-SE but detected as en

Website Classification

Primary Category

social media network96% confidence
Type: spa
Method: ml+structural

All Detected Categories

social media network
96%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
1346.4.25.184Falkenstein, Saxony, Germany
AS24940Hetzner Online GmbH
13192.0.76.3San Francisco, California, United States
AS2635Automattic, Inc
262--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1A753B922836848F5395F8B68854AF31DF19CA5C4DA8953E7F0B5E22454CC6BA24F7B0F

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:Bg5ypt8bAeAeawAXAw8bAMkAtJ23gsk3hpIAddzU8uAff7R91:Bg0BeAeXAXAw+AMkA5skxpIAddA8uAXd

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:66596:AzJ5NwGhxYICEMABnNAiXuhJAS5AAgCgMBjEGgICiHJUIAMgBmOEUGcWARtYkw4AheSAwswgCAbE8HpCwgqFBGCEhRqhTbzQ

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:9dffffc7e7ffffe7
Perceptual Hash:b71e8e1e371c8c0e
Difference Hash:6100000c0c000008
Wavelet Hash:bdff3f03003c3c24
Color Hash:#3a4b78

Other Hashes

Crop Resistant:6100000c0c000008

Scan History

Scan history not available

Unable to load historical scan data