Security Scan Report: my.sinclair.edu

Redirected to:
https://login.microsoftonline.com/f5fdc4e3-1232-4f2a-99e4-0e82ec4902fd...
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Submitted: Jul 18, 2026, 5:35:28 PMCompleted: Jul 18, 2026, 5:36:38 PMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 4 HTTP transactions. The main domain is login.microsoftonline.com and was registered NaN years ago.

Submitted URL: https://my.sinclair.edu

Effective URL: https://login.microsoftonline.com/f5fdc4e3-1232-4f2a-99e4-0e82ec4902fd/saml2?SAMLRequest=fVLJbsIwEP2VyPfEwUkAWwSJwqFItEVAe%2BilMs4ELDk29Tht%2BfuydKGHcp43b5sZoGzMTozasLULeG0BQ%2FTRGIviNChJ661wEjUKKxtAEZRYju5mgiWp2HkXnHKGRCNE8EE7O3YW2wb8EvybVvC4mJVkG8IOBaXNPkFtlZHaJ1C1dLnV67UzELYJoqNHWkbnD8sViSYHH9rKI%2BPvvnEbbZNGK%2B%2FQ1cFZoy0kyjW0LupK5ZDFHZaxOK%2BZjDmHPE6hz0DlPGV1RY%2BBGImmk5K88LrqpjLnsuhnTKVdVlSs1y8ynvKKF7w6wBBbmFoM0oaSsJR147QXd%2FqrTk9khcjYM4nmX%2FlvtK203Vwva30GobhdrebxOeYTeDxFPADIcHB0KE7C%2FuII12nld%2FNk%2BF%2FP%2BNPzgF5InPV24v7AOZ3MndFqH42Mce9jDzJASTqEDs8rfz9k%2BAk%3D&RelayState=ss%3Amem%3A4de3fdead2fa2d1edd312d5525d551e346bed6237f0af7ff818d9b1567abc7c6&sso_reload=trueRedirected

The Cisco Umbrella rank of the primary domain is #365,457 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 92%

2
Risk Score

The page is a legitimate Sinclair University login that redirects to Microsoft’s official SSO service.

Safety Factors
Established domain with long registration history
Uses official Microsoft authentication service
No credential exfiltration or malicious network activity detected
No brand impersonation – site displays its own institutional brand
Domain age information unavailable

Details

Page Title

Sign in to your account

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

documentation technical

(42%)

Domain Information

Domain 'my.sinclair.edu' uses the sponsored educational top-level domain (.edu) and includes subdomain 'my'. Its registrable label 'sinclair' stretches across 8 characters containing 3 vowels alongside 5 consonants. Segmentation suggests 1 word: sinclair. Median word length is eight characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://my.sinclair.edu

Page Load Overview

2.30s
Total Load Time
17
HTTP Requests
5
Domains
982 KB
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:307 chars
Detector Agreement:67%

Website Classification

Primary Category

documentation technical42% confidence
Type: webapp
Method: ml+structural

All Detected Categories

documentation technical
42%

Detected Features

Login Form
Search

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
17140.106.57.75Dayton, Ohio, United States
AS32178Sinclair Community College
171--

Detected Technologies5

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T130834BE57EA3293B878640B5B5797E02AE3659138D4CDDA0F05CCD882FFAB1D8123617

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:DS8GLG2oorvOTc97pHYBooIZ9Tjuokmap5vPoMLuBU+0wPqiAQEC:28horvOTc97p4B4a/AYHQEC

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:81864:IgFOQPEKAEK4FAAiBGUpCGwABkAEoUUSJ0GgAkuWAheBPNFggNhCcDZARQ7UkQcAQjAzbUEijgQClABiFRLEtCiAxCGLChrQ

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:ffcfc3cfffffffff
Perceptual Hash:b3318ccccc673333
Difference Hash:00180c1800000000
Wavelet Hash:ffdfc3cf00000000
Color Hash:#7a2d86

Other Hashes

Crop Resistant:00180c1800000000

Scan History

Scan history not available

Unable to load historical scan data