Security Scan Report: www.unifal-mg.edu.br

Submitted: Nov 16, 2025, 6:22:21 PMCompleted: Nov 16, 2025, 6:23:27 PMpubliccompleted
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Summary

This website contacted 44 IPs in 4 countries across 11 domains to perform 145 HTTP transactions. The main domain is unifal-mg.edu.br and was registered NaN years ago.

Submitted URL: https://www.unifal-mg.edu.br/portal/index/

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Legitimate university website with no apparent security threats.

Safety Factors
Long‑standing domain registration
Educational institution (.edu.br) namespace
Absence of suspicious forms or scripts
No external malicious links
Domain age information unavailable

Details

Page Title

UNIFAL-MG – UNIFAL-MG | Universidade Federal de Alfenas – Minas Gerais

Scan Type

public

Language

🇵🇹

Portuguese

(80% confidence)

Category

social media network

(87%)

Domain Information

Domain 'www.unifal-mg.edu.br' uses the Brazilian country-code top-level domain (.edu.br) with subdomain 'www'. The core label 'unifal-mg' covers 9 characters holding 3 vowels versus 5 consonants, along with 1 hyphen. Word splitting yields 3 words: uni, fal, mg. Expect 3 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://www.unifal-mg.edu.br/portal/index/

Page Load Overview

19.16s
Total Load Time
145
HTTP Requests
11
Domains
2.0 MB
Total Size

Language Analysis

Primary Language

🇵🇹Portuguese
Code: pt
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

Language Code:pt
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:pt-BR
Text Length:475 chars
Detector Agreement:75%

Website Classification

Primary Category

social media network87% confidence
Type: spa
Method: ml+structural

All Detected Categories

social media network
87%
news media journalism
76%
education learning
67%
education
45%
government public service
28%

Detected Features

OG: article

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
16151.101.1.229San Francisco, California, United States
AS54113FASTLY
3104.16.174.226United States
AS13335CLOUDFLARENET
3142.250.184.232United States
AS15169GOOGLE
3216.58.206.74United States
AS15169GOOGLE
354.232.22.6São Paulo, São Paulo, Brazil
AS16509AMAZON-02
315.229.72.199São Paulo, São Paulo, Brazil
AS16509AMAZON-02
3172.217.18.8United States
AS15169GOOGLE
3142.250.186.74United States
AS15169GOOGLE
374.125.133.157United States
AS15169GOOGLE
354.207.60.136São Paulo, São Paulo, Brazil
AS16509AMAZON-02
14544--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T19AC3173E7435193E226F436E9257A30C509DE9B3E912E6FCFBF9090846D9ABA70D7104

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:n32JkWT3SOGA4RjZBXYiDoKDok3tc3kV0t0SyFNVLokOFeoO7u9bINokFmzB+F3d:gGXYEtIn6

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:129069:CB5RvIhAAGSSwLDYHwi+DAQgJYANRwFoGEIUiIjpRoCRBTeoGpAAiJqAVJYCwgTSVgjQsMsCP7EcIlAIAQCIIIHwoR8AeTEI

These hashes enable detection of similar websites and malware variants by comparing content similarity even when exact matches aren't found.

Scan History

Scan history not available

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