Security Scan Report: tischcollege.tufts.edu

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Submitted: Completed: publiccompleted
This website contacted 15 IPs in 2 countries across 8 domains to perform 50 HTTP transactions. The main domain is tufts.edu and was registered 39 years ago.

Submitted URL: https://tischcollege.tufts.edu/take-action/vote/voters-guide-2026-massachusetts-ballot-questions

The Cisco Umbrella rank of the primary domain is #103,812 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 96%

0
Risk Score

Legitimate Tufts University (Tisch College) voter-guide page explaining Massachusetts 2026 ballot questions; no forms beyond site search, no impersonation, and no threat-intel, hunting rule or IDS hits.

Safety Factors (4)
Established .edu domain nearly four decades old with legitimate institutional content
No credential or payment collection anywhere on the page
Cross-origin requests limited to standard Google Analytics/Adobe Typekit/Siteimprove analytics and font hosts
Civic-education content with consistent navigation, mission, resources and contact sections
Domain age information unavailable

Details

Page Title

Voters' Guide to 2026 Massachusetts Ballot Questions | Jonathan M. Tisch College of Civic Life

Scan Type

public

Domain Name Analysis

Domain 'tischcollege.tufts.edu' uses the sponsored educational top-level domain (.edu); it also runs on subdomain 'tischcollege'. The registrable portion 'tufts' spans 5 characters split between one vowel and 4 consonants. It segments into one word: tufts. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://tischcollege.tufts.edu/take-action/vote/voters-guide-2026-massachusetts-ballot-questions

Page Load Overview

1.59s
Total Load Time
1.4 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:23,962 chars
Detector Agreement:100%

Website Classification

Primary Category

government public service50% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

government public service
50%
education
45%

Detected Features

Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
8146.75.123.52Fastly · CDNFrankfurt am Main, Hesse, Germany
AS54113Fastly, Inc.
323.194.190.83Akamai · CDNFrankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
3184.24.77.169Akamai · CDNFrankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
3142.251.20.97Google · CDNUnited States
AS15169Google LLC
3142.251.13.139Google · CDNUnited States
AS15169Google LLC
3188.114.97.3Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
3216.239.32.36Google · CDNUnited States
AS15169Google LLC
33.77.1.212Aws · CLOUDFrankfurt am Main, Hesse, Germany
AS16509Amazon.com, Inc.
3184.24.77.135Akamai · CDNFrankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
323.194.190.74Akamai · CDNFrankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
5015--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1ECA3C6C394E1723A811396F2D36EAAB895349507E3021C4BF07E83991FD6E955BF312E

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:2MCMPMCMfMCM8MCMGMCM/MCMtMCMAsVMJI1hI7v8iBmgpqllmu4LkvywFrehqiYa:H1muOqrehN

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:98780:qOoJ7KSKWJEIGgAhMoAANlgEd7EMUTQCTUzoSYhACUCwCoghHkkxTkEEiQIiKCWEFAp0QxaAA0BRE2pIRNEgEjYAQGQAMaiS

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:0083ffffdfffdfff
Perceptual Hash:bd47436b4246676c
Difference Hash:8216262e3b3b2f3b
Wavelet Hash:0000c3ffc3cfc3cf
Color Hash:#c587b1

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data