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Security Scan Report: med.stanford.edu

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Submitted: Oct 16, 2025, 2:05:27 PMCompleted: Oct 16, 2025, 2:06:46 PMpubliccompleted
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Summary

This website contacted 50 IPs in 3 countries across 14 domains to perform 115 HTTP transactions. The main domain is med.stanford.edu and was registered NaN years ago.

Submitted URL: https://med.stanford.edu/profiles/rebecca-miller

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Legitimate Stanford Medicine profile page with no security concerns.

Safety Factors
Well-established domain (over 40 years old)
Official Stanford Medicine subdomain
No malicious Indicators of Compromise
No credential collection forms
Domain age information unavailable

Details

Page Title

Rebecca Kate Miller-Kuhlmann | Stanford Medicine

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

education

(45%)

Domain Information

Within the sponsored educational top-level domain (.edu), 'med.stanford.edu' is registered with subdomain 'med'. Its registrable label 'stanford' stretches across 8 characters containing 2 vowels alongside 6 consonants. Breaking it apart gives 1 word: stanford. Expect 8 characters per word on average. 'stanford' is most common in Danish usage. It also appears in Indonesian and Icelandic contexts.

Screenshot

Security scan screenshot of https://med.stanford.edu/profiles/rebecca-miller

Page Load Overview

50.03s
Total Load Time
115
HTTP Requests
14
Domains
5.2 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-US
Text Length:34,027 chars
Detector Agreement:100%

Website Classification

Primary Category

education45% confidence
Type: spa
Method: ml+structural

All Detected Categories

education
45%
education learning
43%
corporate
25%
forum
20%

Detected Features

Search
OG: website

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
17142.250.184.228United States
AS15169GOOGLE
2171.67.37.63Palo Alto, California, United States
AS32STANFORD
218.197.64.247Frankfurt am Main, Hesse, Germany
AS16509AMAZON-02
2216.239.34.36United States
AS15169GOOGLE
234.117.178.225Kansas City, Missouri, United States
AS396982GOOGLE-CLOUD-PLATFORM
2142.250.184.232United States
AS15169GOOGLE
263.140.62.236United States
AS16509AMAZON-02
2142.250.185.202United States
AS15169GOOGLE
223.35.236.237Frankfurt am Main, Hesse, Germany
AS16625AKAMAI-AS
2142.250.185.110United States
AS15169GOOGLE
11550--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T16054DA6291F112E6816F3092A2A137D5E67BE30FB3451BE0B4AC429C1F45DD49F372AE

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:5t6nO/Ii2AaDjRlSyDUSnp9CsZUBFMhqSnQiO92sl6DbwWnU+t2mGkf6c:5tsn292m6DbwWnU+t2mGnc

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:286585:MfTsliglBgZhQXhYAMJAEA3lATOKFEZgTQyGBEIE5ILA0B2VJAg2ETABUDAADAQwIeEgIgjsCmLh0UxBwAQJQMJwtAGAiTg6

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:00c381ffffffffff
Perceptual Hash:bd6d129692436d39
Difference Hash:7c37070796969c9c
Wavelet Hash:008181e3ebcbcfcf
Color Hash:#6cc9e0

Other Hashes

Crop Resistant:7c37070796969c9c,0404061c1c040404,2da2922528202088

Scan History

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