Security Scan Report: sf-api-token-service.itunes.apple.com

Submitted: Nov 27, 2025, 9:52:48 AMCompleted: Nov 27, 2025, 9:55:52 AMpubliccompleted
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Summary

This website contacted 7 IPs in 1 country across 1 domain to perform 2 HTTP transactions. The main domain is sf-api-token-service.itunes.apple.com.

Submitted URL: https://sf-api-token-service.itunes.apple.com/

The Cisco Umbrella rank of the primary domain is #13 of the top 1 million websitesTop 100 Site

AI Security Verdict

Safe Website

Confidence: 98%

0
Risk Score

No security concerns detected; site appears legitimate.

Safety Factors
High Cisco Umbrella ranking (13) indicating reputable domain
Domain is a subdomain of official Apple domain (itunes.apple.com)
Domain age information unavailable

Details

Page Title

N/A

Scan Type

public

Domain Information

Domain 'sf-api-token-service.itunes.apple.com' uses the commercial generic top-level domain (.com), featuring subdomain 'sf-api-token-service.itunes'. The core label 'apple' covers 5 characters split between two vowels and 3 consonants. Breaking it apart gives 1 word: apple. Median word length comes out to five characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://sf-api-token-service.itunes.apple.com/

Page Load Overview

0.21s
Total Load Time
2
HTTP Requests
1
Domains
0 KB
Total Size

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
269.192.160.24Frankfurt am Main, Hesse, Germany
AS16625AKAMAI-AS
223.3.108.26Frankfurt am Main, Hesse, Germany
AS16625AKAMAI-AS
02a02:26f0:3500:598::2a1Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
02a02:26f0:3500:584::2a1Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
02a02:26f0:3500:58c::2a1Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
02a02:26f0:3500:594::2a1Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
02a02:26f0:3500:589::2a1Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
27--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T14AD0237AD520051913335AECDE82710C4AD5720ED4325C41B984D06485C7959C403384

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3:qVZxVsws+7L9Hv8+5BuFJYkAK3BbZ6iLDAzd6Nx/dKbUKYS8K4FLfRRyIdlEbXId:qzxV/5VHHQYk/B968ACxEbTYNdxELa

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:1:0:956b908c87e258ce33ec81e2edfdea87

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:00ffffffffffffff
Perceptual Hash:9919191b1f1f0f47
Difference Hash:f020000000000000
Wavelet Hash:00ffffff00000000
Color Hash:#e0966c

Other Hashes

Crop Resistant:f020000000000000

Scan History

Scan history not available

Unable to load historical scan data