Security Scan Report: eprints.uny.ac.id

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Submitted: Sep 30, 2026, 8:58:36 AMCompleted: Sep 30, 2026, 8:59:32 AMpubliccompleted

This website contacted 1 IP in 1 country across 1 domain to perform 2 HTTP transactions. The main domain is eprints.uny.ac.id and was registered 26 years ago.

Submitted URL: https://eprints.uny.ac.id/24190/1/S-4.pdf

The Cisco Umbrella rank of the primary domain is #201,894 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 92%

0
Risk Score

Legitimate academic PDF hosted on the official 26-year-old Universitas Negeri Yogyakarta eprints repository. No forms, no malware patterns, no Indicators of Compromise — no phishing or scam indicators present.

Safety Factors (4)
Established university domain with 26-year registration history
Static PDF file served from an official institutional repository
No forms, no scripts contacting third-party domains, no obfuscated JavaScript
No threat-intelligence matches against the page or its loaded resources
Domain age information unavailable

Details

Page Title

N/A

Scan Type

public

Domain Name Analysis

You're looking at domain 'eprints.uny.ac.id' on the Indonesian country-code top-level domain (.ac.id) and includes subdomain 'eprints'. Count 3 characters in 'uny' containing 1 vowel alongside two consonants. Word splitting yields 2 words: u, ny. Average segment length settles at 1.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://eprints.uny.ac.id/24190/1/S-4.pdf

Page Load Overview

3.80s
Total Load Time
2 KB
Total Size

Language Analysis

Primary Language

🏳️UNKNOWN
Code: unknown
Confidence:0%

Detection Details

0
Detector Agreement:0%

Website Classification

Primary Category

unknown0% confidence
Type: static
Method: structural

All Detected Categories

No categories detected

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2101.203.168.73Indonesia
AS55674Universitas Negeri Yogyakarta
21--

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T17FC080498464501D74243681DDE53611C85EC2513575DEC6B4D619394B5C759484F119

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3:PouVIZx4LyFzT6LTORuWyPDo0GD/1BwqEXDrroYdF0NAEtvpL//X0HKqz:hax4LKT6+8HGD/1BwqEX3kYdF0NAEdpA

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:1:0:e8845dd235ccba766afddb67a1c5641d

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:ff00000000000000
Perceptual Hash:fccdcdccc8c8c8c8
Difference Hash:0000000000000000
Wavelet Hash:fffbf0f0c0c0c0c0
Color Hash:#77862d

Other Hashes

Crop Resistant:0000000000000000

Scan History

Scan history not available

Unable to load historical scan data