Security Scan Report: novafm.com.au

Submitted: Oct 4, 2026, 1:16:31 AMCompleted: Oct 4, 2026, 1:17:07 AMpubliccompleted

This website contacted 28 IPs in 3 countries across 1 domain to perform 3 HTTP transactions. The main domain is novafm.com.au.

Submitted URL: https://novafm.com.au/podcast/the-real-story-with-joe-hildebrand/09efa624-5cec-4d4e-ab7e-ea593c4c19c4/2025-06-25/sarah-harris-on-the-demise-of-the-project

AI Security Verdict

Low Risk

Confidence: 80%

2
Risk Score

Official Nova FM podcast episode page on its own domain with no forms, no impersonation and no threat-intel, YARA or IDS hits. Unknown domain age and scanner bot-block are neutral signals.

Safety Factors (4)
Content is a media/podcast episode with real show description, host, guest and date
Legal pages present (terms & conditions, privacy policy, contact/complaint links)
Own-brand domain consistent with page title and content
No credential or payment collection of any kind
Domain age information unavailable

Details

Page Title

The Real Story With Joe Hildebrand - Sarah Harris On The Demise Of The Project

Scan Type

public

Domain Name Analysis

The domain name 'novafm.com.au' uses the Australian country-code top-level domain (.com.au). The registrable portion 'novafm' spans 6 characters holding two vowels versus four consonants. Splitting it apart reveals 2 words: nova, fm. The median word length lands at three characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://novafm.com.au/podcast/the-real-story-with-joe-hildebrand/09efa624-5cec-4d4e-ab7e-ea593c4c19c4/2025-06-25/sarah-harris-on-the-demise-of-the-project

Page Load Overview

0.54s
Total Load Time
67 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:285 chars
Detector Agreement:100%

Website Classification

Primary Category

documentation technical48% confidence
Type: static
Method: ml+structural

All Detected Categories

documentation technical
48%
technology software
43%
cryptocurrency blockchain
36%
news media journalism
33%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
376.76.21.21Aws · CLOUDWalnut, California, United States
AS16509Amazon.com, Inc.
018.172.112.60Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
034.8.30.44Google · CDNKansas City, Missouri, United States
AS396982Google LLC
032.184.114.169Aws · CLOUDBoardman, Oregon, United States
AS16509Amazon.com, Inc.
0142.251.110.97Google · CDNUnited States
AS15169Google LLC
03.171.214.72Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
03.5.169.18Aws · CLOUDSydney, New South Wales, Australia
AS16509Amazon.com, Inc.
013.226.244.29Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
013.226.244.78Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
0157.240.0.6Facebook · CDNFrankfurt am Main, Hesse, Germany
AS32934Facebook, Inc.
328--

Detected Technologies1

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1CBB41B97854B84395EEA51D953E93F4C766AC207D9A388D9DFF7C6203BC4FE82C68060

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:0pNRIphfXww5omg4EHw1Eq/9t2FTd0nJM:0pNCphfA8gcJ/9t2l

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:498390:PIlkwQRAkAScYySECIABNKJ5SChrgrRiqEBCAJxDgEQjbbkSwTKxxalzkYAj4GBkIAuVjiCjATAQycYAgCAKGEdJGAQIAUgE

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:ff786020243404ff
Perceptual Hash:c2c1bc9ebc30e9d2
Difference Hash:39c1c1c94dedcd1d
Wavelet Hash:ff7c6020242425ff
Color Hash:#7997d2

Scan History

Scan history not available

Unable to load historical scan data