Security Scan Report: usc-visio.wac.trafficmanager.net

Redirected to:
https://m365.cloud.microsoft/
Site favicon
Submitted: Sep 13, 2026, 9:36:09 PMCompleted: Sep 13, 2026, 9:36:36 PMpubliccompleted

This website contacted 23 IPs in 6 countries across 18 domains to perform 65 HTTP transactions. The main domain is m365.cloud.microsoft and was registered 23 years ago.

Submitted URL: https://usc-visio.wac.trafficmanager.net

Effective URL:

https://m365.cloud.microsoft/
Redirected

The Cisco Umbrella rank of the primary domain is #856,810 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Official Microsoft 365/Copilot page reached via redirect to m365.cloud.microsoft; no forms, IoCs, malware, or impersonation detected.

Safety Factors
Final destination is an established Microsoft-owned domain
Page content matches Microsoft 365/Copilot branding and product descriptions
No credential or payment collection forms present
No threat-intelligence, YARA, or malware detections
IDS alert is informational and consistent with Microsoft OAuth activity
Domain age information unavailable

Details

Page Title

Microsoft 365 - Sign into Copilot

Scan Type

public

Domain Name Analysis

The domain name 'usc-visio.wac.trafficmanager.net' uses the network infrastructure generic top-level domain (.net) and includes subdomain 'usc-visio.wac'. The registrable portion 'trafficmanager' spans 14 characters containing five vowels alongside nine consonants. Breaking it apart gives 2 words: traffic, manager. Average segment length settles at 7 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://usc-visio.wac.trafficmanager.net

Page Load Overview

4.29s
Total Load Time
3.3 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en-US
Text Length:18,294 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software88% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
88%
education learning
51%
e-commerce shopping
34%
documentation technical
34%
finance banking
26%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
21150.171.110.49Azure · CLOUDUnited States
AS8075Microsoft Corporation
223.103.241.46Azure · CLOUDFrankfurt am Main, Hesse, Germany
AS8075Microsoft Corporation
223.38.21.121Akamai · CDNHaarlem, North Holland, Netherlands
AS16625Akamai Technologies, Inc.
223.103.241.67Azure · CLOUDFrankfurt am Main, Hesse, Germany
AS8075Microsoft Corporation
223.37.194.81Akamai · CDNBerlin, State of Berlin, Germany
AS16625Akamai Technologies, Inc.
252.108.79.26Office365 · CLOUDDulles, Virginia, United States
AS8075Microsoft Corporation
22.18.27.170Akamai · CDNSlough, England, United Kingdom
AS20940Akamai International B.V.
213.107.246.44Azure · CLOUDUnited States
AS8075Microsoft Corporation
213.107.213.44Azure · CLOUDUnited States
AS8075Microsoft Corporation
22.20.245.176Akamai · CDNFrankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
6523--

Detected Technologies2

40%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T117A15233D0308C06A7209254ADC2B464FA7B42A78648FC91F59F856E5FC5BEAA0D331E

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:fBeQmDejm/+neUmACQUrWFdABIb3+CbQsvHxH9p:feO1eBCbdT

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:4675:ABAACgAKQOkFAYJIAiZAwCAwWAsABQ0QAEIyEcAAECIBAxEiAASqogAACAAAwVAATBIAMAyCRAMAEVAABIFaAwAMkUQMggBB

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:07e381c3e7e7ffbf
Perceptual Hash:b36c8e93346c3b8a
Difference Hash:4d0e2317cc48b068
Wavelet Hash:008080c1e7e7ffbf
Color Hash:#23931f

Other Hashes

Crop Resistant:4d0e2317cc48b068

Scan History

Scan history not available

Unable to load historical scan data