Security Scan Report: www.podcastnewsdaily.com

Site favicon
Submitted: Oct 1, 2026, 12:40:56 PMCompleted: Oct 1, 2026, 12:41:42 PMpubliccompleted

This website contacted 8 IPs in 1 country across 1 domain to perform 2 HTTP transactions. The main domain is podcastnewsdaily.com and was registered 7 years ago.

Submitted URL: https://www.podcastnewsdaily.com/news/fox-news-adds-female-led-conversation-show-to-podcast-lineup/article_59be0693-bf76-458e-bf46-2fa47c15632a.html

AI Security Verdict

Safe Website

Confidence: 88%

1
Risk Score

Established self-branded news site (7+ years old) publishing an editorial article. No forms, no Indicators of Compromise, no malware or IDS hits. Unranked status is a weak prior and no concrete malicious signal exists — safe.

Safety Factors (5)
Established domain age (nearly 8 years) reduces phishing likelihood
Self-branded site with title/meta matching its own domain
No credential, login, or payment forms present
Third-party scripts served from well-ranked hosts (Segment CDN #2,402, Google Fonts, Google Tag Manager)
Standard news-media CMS footprint (TownNews bloximages/vip.townnews.com) consistent with a real publication
Domain age information unavailable

Details

Page Title

Fox News Adds Female-Led Conversation Show To Podcast Lineup. | News | podcastnewsdaily.comother network

Scan Type

public

Domain Name Analysis

You're looking at domain 'www.podcastnewsdaily.com' on the commercial generic top-level domain (.com), featuring subdomain 'www'. The registrable portion 'podcastnewsdaily' spans 16 characters split between five vowels and eleven consonants. It segments into 3 words: podcast, news, daily. The median word length lands at 5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://www.podcastnewsdaily.com/news/fox-news-adds-female-led-conversation-show-to-podcast-lineup/article_59be0693-bf76-458e-bf46-2fa47c15632a.html

Page Load Overview

1.87s
Total Load Time
0 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:50%
Script:Latin
Direction:ltr

Detection Details

Text Length:66 chars
Detector Agreement:100%

Website Classification

Primary Category

news media journalism40% confidence
Type: static
Method: ml+structural

All Detected Categories

news media journalism
40%
healthcare medical
39%
government public service
34%
adult content
27%
news
15%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2192.104.183.109United States
AS10668Lee Enterprises, Incorporated
0104.16.133.24Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
0172.217.208.95Google · CDNUnited States
AS15169Google LLC
0142.251.156.119Google · CDNUnited States
AS15169Google LLC
0142.251.14.97Google · CDNUnited States
AS15169Google LLC
0142.251.14.94Google · CDNUnited States
AS15169Google LLC
0142.251.13.94Google · CDNUnited States
AS15169Google LLC
03.174.47.131Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
28--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T10C04D532A1F124B2026F61D6F265BB5C5A53D747D78153F0F2AC85602FC2E897C672E8

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:36qybabk2x5a8AiVjUxbxa2xKJHQlZB1OeB/gYEskaYPPk4IX:36+wl1/X

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:185013:CEZU0VoBK0JSQSAggnIOQA6AeqEJEDEkMUjGgJNAkqhQEKJKQihUAUBACCIlkT4gBZSUEwNQExSEgOA2AFQEBAJAJAQwDIBs

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:3c3c3838383c3c3c
Perceptual Hash:c369969292966d79
Difference Hash:f8d0d0d0d0d0dcdc
Wavelet Hash:3c3c3878787c3c3c
Color Hash:#6fd22d

Scan History

Scan history not available

Unable to load historical scan data