Security Scan Report: careercenter.bauer.uh.edu

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Submitted: Completed: publiccompleted
This website contacted 15 IPs in 1 country across 10 domains to perform 85 HTTP transactions. The main domain is uh.edu and was registered 39 years ago.

Submitted URL: https://careercenter.bauer.uh.edu/blog/2019/09/09/the-financial-services-industry-for-beginners/

The Cisco Umbrella rank of the primary domain is #59,107 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Legitimate University of Houston Bauer College career-center blog article on financial services careers. Established .edu domain, no credential or payment forms, no threat-intelligence or malware signals.

Safety Factors (5)
Established .edu domain (39 years old) with a University of Houston physical address in the page footer
Article/blog content type with named author and attributed external source
No credential or payment collection on the page — only a same-origin search form
Ranked in Cisco Umbrella top 100K (59,107)
No Indicators of Compromise, hunting-rule matches, or malicious kit indicators
Domain age information unavailable

Details

Page Title

The Financial Services Industry for Beginners – Rockwell Career Center | Bauer College of Business at the University of Houston

Scan Type

public

Domain Name Analysis

The domain 'careercenter.bauer.uh.edu' uses the sponsored educational top-level domain (.edu) and includes subdomain 'careercenter.bauer'. The core label 'uh' covers 2 characters holding one vowel versus one consonant. Tokenizing the label suggests 1 word: uh. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://careercenter.bauer.uh.edu/blog/2019/09/09/the-financial-services-industry-for-beginners/

Page Load Overview

2.18s
Total Load Time
2.3 MB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:en-US
Text Length:8,295 chars
Detector Agreement:100%

Website Classification

Primary Category

education45% confidence
Type: spa
Method: ml+structural

All Detected Categories

education
45%
government public service
28%
forum
25%
news/blog
20%

Detected Features

Search
Comments
OG: article

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
1534.204.213.151Aws · CLOUDAshburn, Virginia, United States
AS14618Amazon.com, Inc.
544.196.168.43Aws · CLOUDAshburn, Virginia, United States
AS14618Amazon.com, Inc.
552.222.236.26Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
5142.250.154.95Google · CDNUnited States
AS15169Google LLC
5192.178.183.97Google · CDNUnited States
AS15169Google LLC
5104.20.42.169Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
5142.251.20.94Google · CDNUnited States
AS15169Google LLC
5216.239.32.36Google · CDNUnited States
AS15169Google LLC
5162.247.243.39Fastly · CDNUnited States
AS54113Fastly, Inc.
5162.247.243.29Fastly · CDNUnited States
AS54113Fastly, Inc.
8515--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T183741B91FD59903A9F7B15BAF14CB23CE21325028F1149E0F25E622A17D1FF287A6E1D

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

6144:u/l5+K5ja/8kr+wddXU2dI+VvVUcckr0VvfG+GSwtAuJqG611CsEeFGWLbGAOUvw:ueK9CSKcweF/vCb

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:359103:zhISNSKRpYgVxwIIErAEUApWgCMQAsYCwkICciDFgVAgJUi3AJAFAAmuFKYN4AgZoqxhAkiBMZ0lJGpEYU+VOw6UNACgDaQA

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:8100cf8f8f8fffdf
Perceptual Hash:b86fc66e38e3848c
Difference Hash:2333381a3a3a3cbc
Wavelet Hash:81008f8f8f8fc71f
Color Hash:#90bf40

Scan History

Scan history not available

Unable to load historical scan data