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Security Scan Report: podcast.app

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Submitted: Oct 27, 2025, 10:16:15 AMCompleted: Oct 27, 2025, 10:19:36 AMpubliccompleted
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Summary

This website contacted 93 IPs in 4 countries across 27 domains to perform 289 HTTP transactions. The main domain is podcast.app and was registered NaN years ago.

Submitted URL: https://podcast.app/

AI Security Verdict

Safe Website

Confidence: 92%

2
Risk Score

The site appears legitimate with standard login functionality and no malicious indicators.

Safety Factors
Established domain age reduces likelihood of phishing
Absence of hidden or disguised password fields
No external links to suspicious domains
No use of IPFS or cloud‑storage hosting which are high‑risk vectors
Standard privacy and cookie notices are present but not suspicious
Domain age information unavailable

Details

Page Title

Podcast App - Listen online to your favorite podcasts

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

unknown

(0%)

Domain Information

The domain name 'podcast.app' uses the application-focused generic top-level domain (.app). Count 7 characters in 'podcast' split between 2 vowels and five consonants. Breaking it apart gives 1 word: podcast. The linguistic tilt is Danish for 'podcast'. It also appears in German and English contexts.

Screenshot

Security scan screenshot of https://podcast.app/

Page Load Overview

0.45s
Total Load Time
289
HTTP Requests
27
Domains
1.9 MB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en
Text Length:8,251 chars
Detector Agreement:100%

Website Classification

Primary Category

unknown0% confidence
Type: spa
Method: structural

All Detected Categories

No categories detected

Detected Features

Login Form

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
215188.114.97.3United States
AS13335CLOUDFLARENET
1352.216.60.33Ashburn, Virginia, United States
AS16509AMAZON-02
8104.18.18.62United States
AS13335CLOUDFLARENET
7150.171.27.10United States
AS8075MICROSOFT-CORP-MSN-AS-BLOCK
7142.250.186.67United States
AS15169GOOGLE
7142.250.186.136United States
AS15169GOOGLE
5157.240.0.35Frankfurt am Main, Hesse, Germany
AS32934FACEBOOK
53.5.8.125United States
AS14618AMAZON-AES
552.242.103.142Boydton, Virginia, United States
AS8075MICROSOFT-CORP-MSN-AS-BLOCK
5216.239.32.36United States
AS15169GOOGLE
28993--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T163B3B6BB100619BE223B9BEA7063EF9FE0558727C66B8C5DF3CD821467CBE905D52244

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:6EnvyN2kEt3/ehzgJ2eJ2ULJ8MYKS0MC2GmECSKcQAACUDY+B9DrlqOWgAGcAuSz:6jN28zgu

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:114280:yDMFBEGLkOoA4gsysAoHAAKaUC+FjYRIEsRTkIAiMAWK4ODAUNEIWDAEAwAgYKkcDIAG/ECQxrAnSkiCBiRUAGQXrEATBggE

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:fe007e7e7e7e0000
Perceptual Hash:97956ec4789195c5
Difference Hash:0ac4c0dcd8d04113
Wavelet Hash:ff007e7e7e7e0000
Color Hash:#6ce092

Other Hashes

Crop Resistant:0ac4c0dcd8d04113,888c585452b0b480,18c4d8d8d4d4cb13,058d8d45058c898b,4b8fcc4c4ccc8d9f

Scan History

Scan history not available

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