ScanMalware.com

Security Scan Report: eg.linkedin.com

Submitted: Completed: publiccompleted

Summary

API
This view is built from:
Scan result: counts, verdicts, details, IPs, technologies, hashes/api/v1/result/c41b8d77-b45c-447f-9281-a1beb44a0e3fDomain and IP registration (RDAP)/api/v1/rdap/c41b8d77-b45c-447f-9281-a1beb44a0e3fHow often this domain was scanned/api/v1/domain/stats/eg.linkedin.comScan history for this domain/api/v1/domain/history/eg.linkedin.com?limit=15
This website contacted 6 IPs in 2 countries across 13 domains to perform 52 HTTP transactions. The main domain is linkedin.com and was registered 24 years ago.

Submitted URL: https://eg.linkedin.com

The Cisco Umbrella rank of the primary domain is #260 of the top 1 million websitesTop 1K Site

AI Security Verdict

Safe Website

Confidence: 96%

0
Risk Score

The site is the legitimate LinkedIn Egypt login page with no security concerns.

Safety Factors (5)
Official subdomain of linkedin.com
Established domain with long registration history
High reputation in Cisco Umbrella rankings
Only email/username fields present, no credential harvesting
No malicious Indicators of Compromise or malware signatures
Domain age information unavailable

Details

Page Title

‏LinkedIn ‏مصر‏: تسجيل الدخول أو إنشاء حساب

Scan Type

public

Domain Name Analysis

Domain 'eg.linkedin.com' uses the commercial generic top-level domain (.com) with subdomain 'eg'. The second-level label 'linkedin' is 8 characters long with 3 vowels and five consonants. Segmentation suggests two words: linked, in. Median word length is four characters. No strong language cues emerged from the frequency lists.

Screenshot

be GihiiimITt =] | oaiooon: avoooor — anoago moon “0000; HUCOOO0 dO U0 OO00O id “ioogonod nocd send sao esi ‘Qo boudo’ion titeoone oor te doetoood tooaCoomt tov Good: (G0 todendt odd coon cccood...

Page Load Overview

1.16s
Total Load Time
781 KB
Total Size

Language Analysis

Primary Language

🇸🇦Arabic
Code: ar
Confidence:80%
Script:Arabic
Direction:rtl

Detection Details

HTML Lang Attribute:ar
Text Length:5,815 chars
Detector Agreement:100%

Website Classification

Primary Category

social media network99% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

social media network
99%
documentation technical
88%
education learning
88%
technology software
87%
government public service
86%

Detected Features

OG: website

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
12146.75.122.133Frankfurt am Main, Hesse, Germany
AS54113Fastly, Inc.
8150.171.109.194United States
AS8075Microsoft Corporation
8104.18.33.206United States
AS13335Cloudflare, Inc.
8104.18.41.41Germany
AS8075Microsoft Corporation
8146.75.123.42Frankfurt am Main, Hesse, Germany
AS54113Fastly, Inc.
8142.251.127.84United States
AS15169Google LLC
526--

Detected Technologies5

Open-Graph-Protocolvwebsite
100%
Azure
50%
Microsoft Power BI
40%
HSTS
40%
Azure Front Door
40%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T147F391D121F41A37055BC9F9B551F624DDE2C92BD24EACA2F28E06526FE5C322D0F26C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:tyb3riJRZ0VjKggAI0UJAd8dRk8ko+T+msKk81SqUO7zCwX1sYR7d5FYzPcG7Cgk:UbijGidgEiHB

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:158462:jAGYkDc1IA2SAkKiBAiqaGWigQIoETAwKEuFQDmKACEAECCwHIDJoqJJb0S5MhoAABCAT8jJZxkDOCJrQ0SaBEWExCkUQMFL

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:00009fffdbdfcfff
Perceptual Hash:bc465338c7b19e2c
Difference Hash:d9b42d2233331258
Wavelet Hash:000000ff9b8fcfff
Color Hash:N/A

Other Hashes

Crop Resistant:d9b42d2233331258,0444d81834311414,6b70f53e73611141

Scan History

Scan history not available

Unable to load historical scan data