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Security Scan Report: learning.cvnl.org

Redirected to: https://bookpdf.co/downloads/4978200-arthur-rinderknech.pdf

Submitted: Oct 10, 2025, 10:52:14 AMCompleted: Oct 10, 2025, 10:53:02 AMpubliccompleted
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Summary

This website contacted 40 IPs in 3 countries across 9 domains to perform 19 HTTP transactions. The main domain is bookpdf.co and was registered NaN years ago.

Submitted URL: https://learning.cvnl.org/index.php/79MmXX/897886/arthur_rinderknech.pdf

Effective URL: https://bookpdf.co/downloads/4978200-arthur-rinderknech.pdfRedirected

AI Security Verdict

Safe Website

Confidence: 80%

2
Risk Score

Site shows no security threats; however, the domain is very new and unranked.

Risk Factors
Very new domain (<30 days)
Unranked domain (not in Cisco Umbrella top 1M)
Safety Factors
No malicious Indicators of Compromise matches
No credential or payment collection forms
No phishing or malware indicators detected
Domain age information unavailable

Details

Page Title

Arthur Rinderknech

Scan Type

public

Language

🇺🇸

English

(51% confidence)

Category

download file sharing

(90%)

Domain Information

The domain 'learning.cvnl.org' uses the non-profit oriented generic top-level domain (.org); it also runs on subdomain 'learning'. The core label 'cvnl' covers 4 characters with 0 vowels and four consonants. Splitting it apart reveals 2 words: cvn, l. Median word length is 2 characters. 'l' most strongly signals Catalan. You will also see it in Chinese (Zhuyin) and Chinese (Simplified) contexts.

Screenshot

Security scan screenshot of https://learning.cvnl.org/index.php/79MmXX/897886/arthur_rinderknech.pdf

Page Load Overview

17.47s
Total Load Time
19
HTTP Requests
9
Domains
182 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:51%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:51%
Script Type:Latin
HTML Lang Attribute:en
Text Length:263 chars
Detector Agreement:100%

Website Classification

Primary Category

download file sharing90% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

download file sharing
90%
adult content
48%
healthcare medical
44%
government public service
42%
news media journalism
42%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
0142.250.185.74United States
AS15169GOOGLE
0142.250.186.131United States
AS15169GOOGLE
0104.20.4.22United States
AS13335CLOUDFLARENET
0104.21.34.95United States
AS13335CLOUDFLARENET
0172.240.253.132United States
AS7979SERVERS-COM
0172.240.108.84United States
AS7979SERVERS-COM
0172.217.18.8United States
AS15169GOOGLE
0144.126.209.130Santa Clara, California, United States
AS14061DIGITALOCEAN-ASN
0188.114.96.3United States
AS13335CLOUDFLARENET
0172.240.108.68United States
AS7979SERVERS-COM
1940--

Detected Technologies2

Debian
40%
Google Analytics
20%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T163520B677B8510257423D1A43DE6AA4F737DD023C10BD8AC7EEC12ACDFC56DA46A6388

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:hRtGxHNij7gVW5yhbpjkboW7oZbFFFoXiQyIQ:RGx2IWwhbpoboW7oZbFFFoQ

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:13834:GyspF4AfKXx0CoUmMEEiKQhTNCgkgACYUaDyaABhASKFxBJJNwDahEHgACoF+UCJJAi0DAAAIn1WUg4EKnZwqVcaCeiCRFxB

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:3c1c3c0000000000
Perceptual Hash:98989836666667de
Difference Hash:71b0704c00000000
Wavelet Hash:ffbd3d3d00000000
Color Hash:#87abc5

Other Hashes

Crop Resistant:71b0704c00000000

Scan History

Scan history not available

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