ScanMalware.com

Security Scan Report: digitalcommons.library.umaine.edu

Submitted: Dec 28, 2025, 8:19:51 AMCompleted: Dec 28, 2025, 8:24:01 AMpubliccompleted
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Summary

This website contacted 15 IPs in 2 countries across 17 domains to perform 155 HTTP transactions. The main domain is digitalcommons.library.umaine.edu and was registered NaN years ago.

Submitted URL: https://digitalcommons.library.umaine.edu/honors/109/

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Legitimate academic page with no security concerns.

Safety Factors
Well‑established academic domain
No data‑collection forms present
No malicious Indicators of Compromise detected
Domain age information unavailable

Details

Page Title

"Robin Hood or Villain: The Social Constructions of Pablo Escobar " by Jenna Bowley

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

government public service

(57%)

Domain Information

The domain 'digitalcommons.library.umaine.edu' uses the sponsored educational top-level domain (.edu); it also runs on subdomain 'digitalcommons.library'. The registrable portion 'umaine' spans 6 characters with four vowels and 2 consonants. It segments into 2 words: u, maine. Expect 3 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://digitalcommons.library.umaine.edu/honors/109/

Page Load Overview

247.53s
Total Load Time
155
HTTP Requests
0
Domains
N/A
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:2,749 chars
Detector Agreement:100%

Website Classification

Primary Category

government public service57% confidence
Type: spa
Method: ml+structural

All Detected Categories

government public service
57%
education
45%

Detected Features

Search
OG: article

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
69104.17.25.14United States
AS13335CLOUDFLARENET
5650.18.241.247San Jose, California, United States
AS16509AMAZON-02
15216.239.32.36United States
AS15169GOOGLE
4172.66.171.172United States
AS13335CLOUDFLARENET
4142.250.186.131United States
AS15169GOOGLE
4142.250.184.202United States
AS15169GOOGLE
323.52.181.12Frankfurt am Main, Hesse, Germany
AS16625AKAMAI-AS
3162.247.243.29United States
AS54113FASTLY
365.9.175.96United States
AS16509AMAZON-02
3142.250.186.168United States
AS15169GOOGLE
015--

Detected Technologies4

Open-Graph-Protocolvarticle
100%
JQueryv1.10.2
100%
Google-Tag-Manager
100%
Google-AnalyticsvUniversal
100%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T127C33A1B5799093EA52321ACB6DAA15D3237B40BE5C0CD54BCEC0214BF86DF0A675FB8

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:kxx2/cmanN+uW8AemApX9B4uOwXYYxpJ2KLupx1QHW5MsXUe75ljRJQaGp:fanPW8AemApXQuOwXYxq2lXpHA

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:127343:CakwGszBJE2gSMA5CEHAqmQQlkAzCABQQYiFhMIGIARrSRUMqDggXIzgKMQJQJBtKuRUCCiIABJi4zQIhQGWYIOCcjDEgtHJ

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:N/A
Perceptual Hash:N/A
Difference Hash:N/A
Wavelet Hash:N/A
Color Hash:N/A

Other Hashes

Crop Resistant:N/A

Scan History

Scan history not available

Unable to load historical scan data