Security Scan Report: getslimms.com

Redirected to:
https://dietoxil.com/
Site favicon
Submitted: Completed: publiccompleted
This website contacted 35 IPs in 4 countries across 20 domains to perform 91 HTTP transactions. The main domain is getslimms.com and was registered 2 years 4 months ago.

Submitted URL: https://getslimms.com/

Effective URL:
https://dietoxil.com/
Redirected

AI Security Verdict

Moderate Risk

Confidence: 62%

4
Risk Score

Supplement landing page with exaggerated weight-loss claims and unverifiable testimonials, but no forms, impersonation or malware signals; treat marketing claims with skepticism.

Risk Factors (3)
Exaggerated weight-loss and digestive-health marketing claims typical of supplement 'health scam' funnels
Customer testimonials with precise kilograms-lost figures and no independent verification
Cross-domain redirect to a different brand/domain weakens accountability of the vendor
Safety Factors (4)
No credential, login or payment form on the captured page (0 forms, 0 password fields, 0 payment fields)
No Indicators of Compromise, YARA matches, Safe Browsing or IDS alerts
No obfuscated JavaScript or credential exfiltration behaviour detected
Page presents its own brand 'Dietoxil' rather than impersonating another entity
Domain age information unavailable

Details

Page Title

Dietoxil

Scan Type

public

Domain Name Analysis

Within the commercial generic top-level domain (.com), 'getslimms.com' is registered while skipping any subdomain. The core label 'getslimms' covers 9 characters split between two vowels and 7 consonants. Segmentation suggests three words: get, slim, ms. Median word length comes out to 3 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://getslimms.com/

Page Load Overview

4.45s
Total Load Time
2.0 MB
Total Size

Language Analysis

Primary Language

🇩🇪German
Code: de
Confidence:41%
Script:Latin
Direction:ltr

Detection Details

Text Length:8,545 chars
Detector Agreement:67%

Website Classification

Primary Category

healthcare medical94% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

healthcare medical
94%
adult content
62%
education learning
53%
government public service
53%
blog personal website
36%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
23104.21.95.36Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
2172.66.41.16Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
217.253.57.206Frankfurt am Main, Hesse, Germany
AS6185Apple Inc.
223.45.238.249Akamai · CDNFrankfurt am Main, Hesse, Germany
AS16625Akamai Technologies, Inc.
2216.198.54.3Cloudflare · CDNUnited States
AS209242Cloudflare London, LLC
2104.18.3.36Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
220.250.198.32Azure · CLOUDZurich, Zurich, Switzerland
AS8075Microsoft Corporation
2142.251.20.97Google · CDNUnited States
AS15169Google LLC
2150.171.109.107Azure · CLOUDUnited States
AS8075Microsoft Corporation
252.167.81.85Azure · CLOUDBoydton, Virginia, United States
AS8075Microsoft Corporation
9135--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1C3141A6EA645013F6C2B86F0D1F4BD5D702BB0C9DF3E52F5BA9221218BC46F72C61A18

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:9ZdiR5Rprm+FKkWgQZwcbnbmIAiASBR1/OBcsOWJyziMuCDn9Y1xsS/eTA/NbG5Q:9E5Rprm+FKkWgQZwcbnbmIAiASBR1/Of

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:190872:6coMokhpAsgDJGYIBuG4AClCMgTEoAmJzUqlKwhImkhvYZIlAUhdIizoAiDKVhIFgmAsIFhhCxKFXEEREgSwB0pIUAzCIQCW

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:bfff9f9391919980
Perceptual Hash:ed92d36d341f110d
Difference Hash:62123a3737332333
Wavelet Hash:a3ff9f8791919180
Color Hash:#35d22d

Scan History

Scan history not available

Unable to load historical scan data