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Security Scan Report: med.admit.org

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Submitted: Dec 31, 2025, 5:34:50 PMCompleted: Dec 31, 2025, 5:36:31 PMpubliccompleted
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Summary

This website contacted 11 IPs in 2 countries across 8 domains to perform 83 HTTP transactions. The main domain is med.admit.org and was registered NaN years ago.

Submitted URL: https://med.admit.org/cycle-results/vanderbilt-university-school-of-medicine

The Cisco Umbrella rank of the primary domain is #271,839 of the top 1 million websites

AI Security Verdict

Low Risk

Confidence: 80%

4
Risk Score

Site appears legitimate but shows Vanderbilt branding on a third‑party domain with a login form.

Risk Factors
Brand name displayed on a non‑official domain
Credential collection form on a third‑party domain
Safety Factors
Domain age > 20 years (well‑established)
No malicious Indicators of Compromise detected
Domain is not newly registered
Domain age information unavailable

Details

Page Title

Vanderbilt University - Cycle Results – Admit.org

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

forum community discussion

(54%)

Domain Information

The domain name 'med.admit.org' uses the non-profit oriented generic top-level domain (.org), featuring subdomain 'med'. Count 5 characters in 'admit' holding 2 vowels versus three consonants. Tokenizing the label suggests 1 word: admit. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://med.admit.org/cycle-results/vanderbilt-university-school-of-medicine

Page Load Overview

11.65s
Total Load Time
50
HTTP Requests
8
Domains
1.2 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:1,914 chars
Detector Agreement:80%

Website Classification

Primary Category

forum community discussion54% confidence
Type: spa
Method: ml+structural

All Detected Categories

forum community discussion
54%
education learning
36%
adult content
33%
healthcare medical
31%
corporate
25%

Detected Features

Login Form
Search
OG: website
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
10188.114.97.3United States
AS13335CLOUDFLARENET
466.241.124.189United States
AS40509FLY
465.9.175.117Switzerland
AS8075
4216.58.206.40United States
AS15169GOOGLE
4216.58.206.59Switzerland
AS16509
4216.239.34.36United States
AS15169GOOGLE
4216.239.32.36SwitzerlandUnknown
420.250.198.32Zurich, Zurich, Switzerland
AS8075MICROSOFT-CORP-MSN-AS-BLOCK
4142.250.185.219United States
AS15169GOOGLE
4188.114.96.3United States
AS13335CLOUDFLARENET
5011--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1A934E75EE103D149ED2F3A5BD5F3BE6A312A48B74B0DCC34DA5DA535049B8B43A27AC0

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:EvFLuAYrf46jDxAZvCr2jfV3pSjuantZ0gyUMhC2QCjh4ZXxwRO2vaBTI8hXFFFJ:EvInvjDwHSKantZ0gyUMhsAma3Bis0

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:243207:AEBkAARpEqSJRwLkskPifMFqUxMAE3WOgQZEQEjazSBFloOAoBWGgCyDMCCI3CXQAFCxsQihpACQSBAIkABiEoeMwAmFwagS

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:0818181818181800
Perceptual Hash:8898763435c767c7
Difference Hash:b0b1b3b3b3b1b1a3
Wavelet Hash:0e1d59595f597d40
Color Hash:#3a3d78

Other Hashes

Crop Resistant:b0b1b3b3b3b1b1a3

Scan History

Scan history not available

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