Security Scan Report: iip.ufrn.br

Submitted: Apr 20, 2026, 10:30:13 AMCompleted: Apr 20, 2026, 10:31:29 AMpubliccompleted
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Summary

This website contacted 2 IPs in 2 countries across 3 domains to perform 1 HTTP transaction. The main domain is iip.ufrn.br and was registered NaN years ago.

Submitted URL: https://iip.ufrn.br/en/about/iac/david-gross

The Cisco Umbrella rank of the primary domain is #431,011 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 93%

1
Risk Score

The site appears legitimate with no phishing, credential harvesting, or malware indicators.

Safety Factors
Well‑established university domain
No suspicious external links to malicious IP
Low Cisco Umbrella ranking does not matter without brand impersonation
No forms or credential collection
Domain age information unavailable

Details

Page Title

David Gross | IIP

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

unknown

(0%)

Domain Information

The domain 'iip.ufrn.br' uses the Brazilian country-code top-level domain (.br), featuring subdomain 'iip'. Its registrable label 'ufrn' stretches across 4 characters with 1 vowel and three consonants. Breaking it apart gives two words: uf, rn. The median word length lands at two characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://iip.ufrn.br/en/about/iac/david-gross

Page Load Overview

3.13s
Total Load Time
57
HTTP Requests
3
Domains
188 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:2,105 chars
Detector Agreement:100%

Website Classification

Primary Category

unknown0% confidence
Type: spa
Method: structural

All Detected Categories

No categories detected

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
29216.198.79.65United States
AS16509Amazon.com, Inc.
28177.20.148.18Natal, Rio Grande do Norte, Brazil
AS262857UNIVERSIDADE FEDERAL DO RIO GRANDE DO NORTE
572--

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T15FA3E8DA9714DA9C685F4C9D6F3EAD3C904EE177FAB6C950C28DCA14448B874FB4AC80

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:y16NQ1h181Y191F1J1E1A11t11O1181gl11b411w1dwDcHVa755n51Ic3EH11onr:zscHcn51Ic3EH3ycn51IcA

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:102262:ZFIAQLAqQgFCkCqAKLgIg5gUNGQQwBaAcAowKQEYMgaCA4AXUBG8HlBBsSCwUKgyZgPSAcITHMgkQJBESJQAhSBVCFUgEAQR

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:00ffffffff000000
Perceptual Hash:b0bf10603f780f1f
Difference Hash:b60c680e32959565
Wavelet Hash:00ffffffff000000
Color Hash:#40d22d

Scan History

Scan history not available

Unable to load historical scan data