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Security Scan Report: scikit-learn.org

Redirected to: https://scikit-learn.org/stable/

Submitted: Mar 15, 2026, 11:48:44 AMCompleted: Mar 15, 2026, 11:49:58 AMpubliccompleted
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Summary

This website contacted 4 IPs in 1 country across 4 domains to perform 1 HTTP transaction. The main domain is scikit-learn.org and was registered NaN years ago.

Submitted URL: https://scikit-learn.org

Effective URL: https://scikit-learn.org/stable/Redirected

The Cisco Umbrella rank of the primary domain is #290,413 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 96%

0
Risk Score

Legitimate scikit-learn documentation site with no security concerns.

Safety Factors
Well‑established domain (over 14 years old)
No credential or payment forms present
No malicious Indicators of Compromise detected
Standard hosting environment
HTTPS connection (secure transport)
Domain age information unavailable

Details

Page Title

scikit-learn: machine learning in Python — scikit-learn 1.8.0 documentation

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

technology software

(68%)

Domain Information

Within the non-profit oriented generic top-level domain (.org), 'scikit-learn.org' is registered while skipping any subdomain. Its registrable label 'scikit-learn' stretches across 12 characters split between four vowels and 7 consonants, notching 1 hyphen. Tokenizing the label suggests 3 words: sci, kit, learn. Average segment length settles at three characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://scikit-learn.org

Page Load Overview

0.94s
Total Load Time
70
HTTP Requests
4
Domains
132 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en
Text Length:3,999 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software68% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

technology software
68%
documentation technical
44%

Detected Features

Search

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
19172.217.20.138United States
AS15169Google LLC
1751.81.254.11Hillsboro, Oregon, United States
AS16276OVH SAS
17185.199.111.153United States
AS54113Fastly, Inc.
17185.199.109.153United States
AS54113Fastly, Inc.
704--

Detected Technologies3

GitHub Pages
40%
Fastly
40%
Font Awesome
20%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1B053F8B350E0613F4A438ADA568C2A1CADB5DA93D9521C95B17E02589FC3FE4232772F

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:wMCMPMCMfMCM8MCMGMCM/MCMtMCMAsVMZI71Aoi8q44c39G8q4S/hFGvRLfV5:WhT6ETcd5

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:63951:QtyjojMks4MABlFTEyiEVsJAIQgEBSZE8CzEStARSCJLHJ5CGBHJEQkyhMrZcgxNAgDEPJCmIYcYRkQhCD5OAQgipqJAgAkA

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:0f00ffff999981ff
Perceptual Hash:bd000338c1e7f9fa
Difference Hash:7ef6720a3b3b2b6b
Wavelet Hash:0600bfeb999981fb
Color Hash:#c5879c

Other Hashes

Crop Resistant:7ef6720a3b3b2b6b,fffffffffffeffff,71d3249412934c64

Scan History

Scan history not available

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