Security Scan Report: nokia.sharepoint.com

Redirected to:
https://login.microsoftonline.com/5d471751-9675-428d-917b-70f44f9630b0...
Site favicon
Submitted: Oct 2, 2026, 9:28:52 PMCompleted: Oct 2, 2026, 9:29:29 PMpubliccompleted

This website contacted 13 IPs in 5 countries across 7 domains to perform 18 HTTP transactions. The main domain is login.microsoftonline.com and was registered 35 years ago.

Submitted URL: https://nokia.sharepoint.com

Effective URL:

https://login.microsoftonline.com/5d471751-9675-428d-917b-70f44f9630b0...
Redirected

The Cisco Umbrella rank of the primary domain is #66 of the top 1 million websitesTop 100 Site

AI Security Verdict

Safe Website

Confidence: 97%

0
Risk Score

Official Microsoft sign-in page for Nokia SharePoint; legitimate SSO redirect with no phishing or malware indicators.

Safety Factors (5)
Official Microsoft authentication infrastructure
Legitimate OAuth/SSO redirect for a SharePoint tenant
No phishing or malware indicators detected
No disguised password fields or payment fields
Established Microsoft-owned login domain
Domain age information unavailable

Details

Page Title

Sign in to your account

Scan Type

public

Domain Name Analysis

Domain 'nokia.sharepoint.com' uses the commercial generic top-level domain (.com); it also runs on subdomain 'nokia'. The registrable portion 'sharepoint' spans 10 characters containing four vowels alongside six consonants. Splitting it apart reveals two words: share, point. Expect 5 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://nokia.sharepoint.com

Page Load Overview

2.11s
Total Load Time
692 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:109 chars
Detector Agreement:67%

Website Classification

Primary Category

unknown0% confidence
Type: webapp
Method: structural

All Detected Categories

No categories detected

Detected Features

Login Form
Search

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
620.190.160.17Office365 · CLOUDAmsterdam, North Holland, Netherlands
AS8075Microsoft Corporation
113.107.136.10Office365 · CLOUDRedmond, Washington, United States
AS8075Microsoft Corporation
140.126.31.2Azure · CLOUDDublin, Leinster, Ireland
AS8075Microsoft Corporation
123.207.210.132Akamai · CDNFrankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
113.107.246.61Azure · CLOUDUnited States
AS8075Microsoft Corporation
140.79.141.156Azure · CLOUDParis, Île-de-France, France
AS8075Microsoft Corporation
113.107.138.10Azure · CLOUDRedmond, Washington, United States
AS8075Microsoft Corporation
120.190.160.65Office365 · CLOUDAmsterdam, North Holland, Netherlands
AS8075Microsoft Corporation
140.126.32.136Azure · CLOUDAmsterdam, North Holland, Netherlands
AS8075Microsoft Corporation
113.107.246.60Azure · CLOUDUnited States
AS8075Microsoft Corporation
1813--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T18BA38DEA7EB61937838A41B5B5BA7D029E766903994CDCA0F14CCD842FFB74C8123647

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:j388GLG2ZDBKL6uZDBDhDKWoguJmpTIZ9Tjuokmap5vPoMLuBo0LepieDxC:b886Bq6MV1KHhmp2a/AqxC

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:101215:hDNIQMHhZYkA9iARAwFQNwoXAwmBAgICDRFgABoAa+EKVYOAoEQIoBKWh8GQalAojRl5kBCM50hnsBCSzcsSAakFoEYAoGwc

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:0000181818180000
Perceptual Hash:c98c3236cc5b99cd
Difference Hash:17b1b33332320a03
Wavelet Hash:035d3938be9ec8e1
Color Hash:#d22d88

Scan History

Scan history not available

Unable to load historical scan data