Security Scan Report: professional.dce.harvard.edu

Redirected to: https://professional.dce.harvard.edu/blog/make-your-speech-all-about-the-audience/#Analyze-the-Audience

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Submitted: Dec 7, 2025, 1:45:11 PMCompleted: Dec 7, 2025, 1:48:39 PMpubliccompleted
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Summary

This website contacted 110 IPs in 4 countries across 34 domains to perform 137 HTTP transactions. The main domain is professional.dce.harvard.edu and was registered NaN years ago.

Submitted URL: https://professional.dce.harvard.edu/blog/make-your-speech-all-about-the-audience/

Effective URL: https://professional.dce.harvard.edu/blog/make-your-speech-all-about-the-audience/#Analyze-the-AudienceRedirected

The Cisco Umbrella rank of the primary domain is #23,419 of the top 1 million websites

AI Security Verdict

Low Risk

Confidence: 95%

2
Risk Score

Legitimate Harvard page with low risk; circular redirect noted but no malicious activity.

Risk Factors
Circular redirect detected
Safety Factors
Domain is well‑established (over 40 years old) and belongs to Harvard University
No malicious Indicators of Compromise matches found
No credential or payment forms on the page
Cisco Umbrella ranking within top 100 K
Domain age information unavailable

Details

Page Title

Make Your Speech All about the Audience - Professional & Executive Development | Harvard DCE

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

corporate business

(64%)

Domain Information

The domain 'professional.dce.harvard.edu' uses the sponsored educational top-level domain (.edu) and includes subdomain 'professional.dce'. Count 7 characters in 'harvard' holding two vowels versus five consonants. It segments into 1 word: harvard. Median word length comes out to seven characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://professional.dce.harvard.edu/blog/make-your-speech-all-about-the-audience/

Page Load Overview

1.00s
Total Load Time
137
HTTP Requests
34
Domains
3.8 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-us
Text Length:13,679 chars
Detector Agreement:100%

Website Classification

Primary Category

corporate business64% confidence
Type: spa
Method: ml+structural

All Detected Categories

corporate business
64%
education
45%
social media network
39%
news/blog
35%
government public service
30%

Detected Features

Search
Articles
OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
33157.240.0.35Frankfurt am Main, Hesse, Germany
AS32934FACEBOOK
2923.185.0.1United States
AS54113FASTLY
16150.171.22.12United States
AS8075MICROSOFT-CORP-MSN-AS-BLOCK
6104.18.87.42United States
AS13335CLOUDFLARENET
5142.250.184.200United States
AS15169GOOGLE
5104.19.147.8United States
AS13335CLOUDFLARENET
4216.239.34.36United States
AS15169GOOGLE
4104.17.92.187United States
AS13335CLOUDFLARENET
313.33.52.91New York, New York, United States
AS16509AMAZON-02
3157.240.0.6Frankfurt am Main, Hesse, Germany
AS32934FACEBOOK
137110--

Detected Technologies11

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1F5941A97276153B8D5C7C398D62224947911D8DBFD7384ECF31D0B74CBC8AEA8C1AA86

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:GyDp0DpSc16M2FsE3z5BtrkAzO6YMFhZ46hKHGy9Ne206:v21l2Fs45BdkAaDMe6hQS23

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:424666:Bhp4wlAgVQE3JQ0Ak2AMBATByUSykjRyLhBigUAoJkAmqhilBMkKADUywNBZHEJxAAQCoFBboYyx8AShYMgCLkgYAAXREkgK

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

Image Hashes

Scan History

Scan history not available

Unable to load historical scan data