Security Scan Report: www.seattlepi.com

Submitted: Oct 7, 2025, 3:11:57 PMCompleted: Oct 7, 2025, 3:12:51 PMpubliccompleted
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Summary

This website contacted 10 IPs in 2 countries across 6 domains to perform 16 HTTP transactions. The main domain is seattlepi.com and was registered NaN years ago.

Submitted URL: https://www.seattlepi.com/sports/article/naomi-osaka-rallies-to-beat-leylah-fernandez-at-21088013.php

The Cisco Umbrella rank of the primary domain is #420,740 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Legitimate site with no security concerns.

Safety Factors
Well‑established domain with long registration history
No malicious Indicators of Compromise matches
No credential or payment collection forms
Domain age information unavailable

Details

Bot Protection Detected

This website is protected by captcha bot protection. Our scanner was challenged or blocked during access.

Page Title

Access to this page has been denied

Scan Type

public

Language

🇺🇸

English

(53% confidence)

Category

documentation technical

(32%)

Domain Information

The domain 'www.seattlepi.com' uses the commercial generic top-level domain (.com) and includes subdomain 'www'. Count 9 characters in 'seattlepi' with 4 vowels and 5 consonants. Segmentation suggests 2 words: seattle, pi. Average segment length settles at 4.5 characters. Most frequently, 'seattle' shows up in Sinhala. It also appears in Albanian and Catalan contexts. Net impression: Sinhala phrase.

Screenshot

Security scan screenshot of https://www.seattlepi.com/sports/article/naomi-osaka-rallies-to-beat-leylah-fernandez-at-21088013.php

Page Load Overview

9.54s
Total Load Time
16
HTTP Requests
6
Domains
684 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:53%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:53%
Script Type:Latin
HTML Lang Attribute:en
Text Length:142 chars
Detector Agreement:100%

Website Classification

Primary Category

documentation technical32% confidence
Type: static
Method: ml+structural

All Detected Categories

documentation technical
32%
healthcare medical
29%
news media journalism
28%
adult content
27%
news
15%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
134.36.73.246Kansas City, Missouri, United States
AS396982GOOGLE-CLOUD-PLATFORM
134.120.250.63Kansas City, Missouri, United States
AS396982GOOGLE-CLOUD-PLATFORM
1142.250.185.202United States
AS15169GOOGLE
123.207.210.139Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
1146.75.122.133Frankfurt am Main, Hesse, Germany
AS54113FASTLY
1146.75.120.200Frankfurt am Main, Hesse, Germany
AS54113FASTLY
123.207.210.143United StatesUnknown
12a02:26f0:7100::687e:25d1United StatesUnknown
12a00:1450:4001:82f::200aUnited StatesUnknown
12a02:26f0:7100::213:c6f1United StatesUnknown
1610--

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T130F1A6334D1A101BE587416D36736E88A6658002FB1792B87CEEE128DFEDBD1CE52F64

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:noGi4fIGbnpBjpt5grJxTyFoTepRNZh92Wefnv7lmoC9EsIgNdH2tEml87vZ6f:zrrn9ter/qVpZSWToC9EW5LUf

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:7535:ACAE4iYJiCYAAEHKgUUAA1DIEQCAu3CAKTSB0y+CwKaQrx6RQNCETEpAkAFIiEARVAAgge4FBADBCGRBEgRPAA7DloGjEgYg

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:ffffffefe7ffffff
Perceptual Hash:b38ccc3333cccc33
Difference Hash:0000102848000000
Wavelet Hash:c3c3ffc72f030303
Color Hash:#96c587

Other Hashes

Crop Resistant:0000102848000000

Scan History

Scan history not available

Unable to load historical scan data