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Security Scan Report: libguides.rccc.edu

Submitted: Sep 2, 2026, 10:49:40 PMCompleted: Sep 2, 2026, 10:50:59 PMpubliccompleted

Summary

This website contacted 28 IPs in 1 country across 13 domains to perform 2 HTTP transactions. The main domain is libguides.rccc.edu and was registered 21 years ago.

Submitted URL: https://libguides.rccc.edu/terrorism/definingterrorism

AI Security Verdict

Safe Website

Confidence: 92%

1
Risk Score

The page is a legitimate library research guide with no malicious signals.

Safety Factors
Established domain with long registration history
Absence of credential or payment collection
No malicious JavaScript or external exploit indicators
No threat intelligence matches
Domain age information unavailable

Details

Page Title

Defining Terrorism - Terrorism - Research Guides at Rowan-Cabarrus Community College

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

education

(90%)

Domain Information

The domain name 'libguides.rccc.edu' uses the sponsored educational top-level domain (.edu); it also runs on subdomain 'libguides'. Count 4 characters in 'rccc' with zero vowels and four consonants. Tokenizing the label suggests 2 words: r, ccc. Median word length comes out to two characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://libguides.rccc.edu/terrorism/definingterrorism

Page Load Overview

9.13s
Total Load Time
56
HTTP Requests
13
Domains
1.8 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:4,977 chars
Detector Agreement:100%

Website Classification

Primary Category

education90% confidence
Type: spa
Method: structural

All Detected Categories

education
90%

Detected Features

Search
OG: website

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2104.18.11.207Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
2151.101.129.155Fastly · CDNUnited States
AS54113Fastly, Inc.
23.86.37.148Aws · CLOUDAshburn, Virginia, United States
AS14618Amazon.com, Inc.
254.87.234.89Aws · CLOUDAshburn, Virginia, United States
AS14618Amazon.com, Inc.
218.173.206.127Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
216.15.246.223Aws · CLOUDAshburn, Virginia, United States
AS14618Amazon.com, Inc.
2142.251.14.95Google · CDNUnited States
AS15169Google LLC
299.84.152.25Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
234.194.39.199Aws · CLOUDAshburn, Virginia, United States
AS14618Amazon.com, Inc.
234.196.10.250Aws · CLOUDAshburn, Virginia, United States
AS14618Amazon.com, Inc.
5628--

Page Statistics

56
Requests
13
Unique Domains
2.0 MB
Total Size

Detected Technologies6

X-UA-Compatible
100%
Open-Graph-Protocolvwebsite
100%
JQueryv3.7.1
100%
HSTS
40%
jQuery UI
20%
jQuery CDN
20%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1C97153132895CD0723304199EB9A715CC593AC5B8E388BD0F4DB1146AEF9FC589F3236

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

48:TTpEHDaZS4Y/68zAMar4gOAE4d6EL7LEpBYKJJGb8bcTpN:TaHESsrsbBYKqUcTpN

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:3610:AACGKAACkAgikIAQAAIhAEIAAABAALMAEQACKAEQAAAgDGIBAiGAEcATKCURAJAMMCQABAQAgAgADBBAACARRCABIKBMQgCA

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:8181bfffc3c3ffff
Perceptual Hash:be2f4f309b92a44a
Difference Hash:270727391f961539
Wavelet Hash:818181df81c3ddfd
Color Hash:#bf4240

Other Hashes

Crop Resistant:270727391f961539,2b4bcb9b13dbdba3,004020202020c000,2bcacb93576acb33,0141a10911c9c949

Scan History

Scan history not available

Unable to load historical scan data