Security Scan Report: uncgspartans.com

Redirected to: https://uncgspartans.com/sports/womens-basketball/stats/2025-26/stanford/boxscore/9750

Submitted: Nov 5, 2025, 5:06:15 AMCompleted: Nov 5, 2025, 5:09:28 AMpubliccompleted
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Summary

This website contacted 173 IPs in 3 countries across 57 domains to perform 398 HTTP transactions. The main domain is uncgspartans.com and was registered NaN years ago.

Submitted URL: https://uncgspartans.com/boxscore.aspx?id=9750

Effective URL: https://uncgspartans.com/sports/womens-basketball/stats/2025-26/stanford/boxscore/9750Redirected

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Legitimate university sports page with no security concerns.

Safety Factors
Long‑standing domain registration
Official UNC Greensboro athletics site
No suspicious redirects or hidden fields
Domain age information unavailable

Details

Bot Protection Detected

This website is protected by imperva bot protection. Our scanner was challenged or blocked during access.

Page Title

Women's Basketball vs Stanford on 11/3/2025 - Box Score - UNC Greensboro

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

unknown

(0%)

Domain Information

The domain 'uncgspartans.com' uses the commercial generic top-level domain (.com) with no subdomain. Count 12 characters in 'uncgspartans' with 3 vowels and 9 consonants. Tokenizing the label suggests 3 words: unc, g, spartans. Median word length comes out to 3 characters. The linguistic tilt is English for 'unc'. Secondary signals appear in Malay and Chinese (Pinyin). Net impression: English phrase.

Screenshot

Security scan screenshot of https://uncgspartans.com/boxscore.aspx?id=9750

Page Load Overview

10.10s
Total Load Time
398
HTTP Requests
57
Domains
3.2 MB
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:17,544 chars
Detector Agreement:100%

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
8065.8.131.84United States
AS16509AMAZON-02
54142.250.186.33United States
AS15169GOOGLE
3454.192.87.149United States
AS16509AMAZON-02
1745.223.123.204United States
AS19551INCAPSULA
12104.17.24.14United States
AS13335CLOUDFLARENET
6142.250.186.46United States
AS15169GOOGLE
6142.250.186.131United States
AS15169GOOGLE
6216.239.32.36United States
AS15169GOOGLE
6216.58.206.40United States
AS15169GOOGLE
5172.64.147.18United States
AS13335CLOUDFLARENET
398173--

Detected Technologies5

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1B0B44544C8E21B7B448BD5D3A9785E2C20F39907CB065406BBDCA7FF3791E48AA4276D

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:194NpONo+OTJovI4BDHPBw5DhXOZ4gH9uRdDGKWvZs8dQCeQn9MGdHZRxmQHZd3n:7gK57CfYlX

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:500000:AQCa5UEBRCLygg2yAAQEwKJEgQBmAAps2CMkgskIAAFYCsQ0JmE9RKCjEGY1tWLfgDVGw8WkEQYANIuHE1hAJAQYLKEQCCQB

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:ff8181fff7ffefff
Perceptual Hash:af6a91c4c491cd2f
Difference Hash:002b3b4467475b4b
Wavelet Hash:ff818181b3e381af
Color Hash:#93441f

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data