Security Scan Report: cgi.s-ed1.cloud.gcore.lu

Submitted: Sep 22, 2026, 2:45:02 PMCompleted: Sep 22, 2026, 2:45:21 PMpubliccompleted

This website contacted 16 IPs in 3 countries across 9 domains to perform 14 HTTP transactions. The main domain is cgi.s-ed1.cloud.gcore.lu and was registered 20 years ago.

Submitted URL: https://cgi.s-ed1.cloud.gcore.lu/O365.html

The Cisco Umbrella rank of the primary domain is #896,168 of the top 1 million websites

AI Security Verdict

Low Risk

Confidence: 96%

3
Risk Score

This is an ordinary sign-in page on a long-established, well-ranked domain, with credentials submitted to a host the operator controls.

Risk Factors (3)
Microsoft-branded credential capture page hosted on an unrelated gcore.lu subdomain
Multi-source threat-intel malware report (silverfox) against the hosting domain
Microsoft trademarks, styling and UI copied without authorization
Safety Factors (2)
Hosting domain is 2888 days old (does not mitigate an active phishing kit on it)
The site's own login form (credentials submit to its own domain; 2888 days old, Cisco Umbrella #896,168) with no strong malicious indicators — a first-party sign-in is normal; risk clamped from 10 to 3
Domain age information unavailable

Details

Page Title

Microsoft | Login

Scan Type

public

Domain Name Analysis

The domain 'cgi.s-ed1.cloud.gcore.lu' uses the Luxembourgish country-code top-level domain (.lu) and includes subdomain 'cgi.s-ed1.cloud'. Count 5 characters in 'gcore' holding 2 vowels versus 3 consonants. Tokenizing the label suggests two words: g, core. Median word length is 2.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://cgi.s-ed1.cloud.gcore.lu/O365.html

Page Load Overview

1.06s
Total Load Time
646 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:55%
Script:Latin
Direction:ltr

Detection Details

Text Length:380 chars
Detector Agreement:100%

Website Classification

Primary Category

social media network78% confidence
Type: dynamic
Method: ml+structural+ocr_tiebreaker

All Detected Categories

social media network
78%
technology software
67%
documentation technical
52%
finance banking
40%
adult content
39%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
14185.145.113.133Luxembourg, Luxembourg, Luxembourg
AS199524G-Core Labs S.A.
0151.101.193.155Fastly · CDNUnited States
AS54113Fastly, Inc.
0172.217.208.95Google · CDNUnited States
AS15169Google LLC
0172.67.142.245Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
013.107.246.44Azure · CLOUDUnited States
AS8075Microsoft Corporation
0104.17.25.14Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
0104.18.10.207Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
0142.251.14.95Google · CDNUnited States
AS15169Google LLC
0195.80.159.133France
AS29152Decknet SARL
0185.145.113.131Luxembourg, Luxembourg, Luxembourg
AS199524G-Core Labs S.A.
1416--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1A374A661CE4B2C51CBA44617F9DD39E10E2D27CEB8E211CD8A0BF7AAC34EC2A65D41D5

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

6144:TR/AmwYJdbz53UJx2g7GbgKymQTBQYDuozI9RsDfnNbHS:zz53W751TBQYPzIS/NbS

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:355010:gQjYUEWSYAhgAUYaBsEAUwEDlugHoeREQ0DMzUSggQYCqbDCIUcBAuwAMCFFgDpJBixZg6ATGQIxUGOIJMEggAKIMC7SAqQA

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:bf3d19191f1fff00
Perceptual Hash:9cc933b366e62691
Difference Hash:71737135797d7979
Wavelet Hash:bf3919111f1f9f00
Color Hash:#bf7740

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data