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Pixalate’s Q1 2025 Report Finds 26% of CTV Bundle IDs Were Malformed, Unidentified, and/or Fraudulent Across Roku, Amazon Fire TV, Apple TV, & Samsung Smart TV

Apr 23, 2025 1:00:00 PM

Pixalate’s data science team analyzed over 2 billion open programmatic advertising impressions across 14k+ CTV Bundle IDs mapped to 6k+ unique apps in March 2025 to compile the research in this series

LONDON, April 23, 2025 – Pixalate, the global market-leading ad fraud protection, privacy, and compliance analytics platform, today released the Q1 2025 Connected TV (CTV) Malformed and Fraudulent Bundle IDs Risk Reports for Amazon Fire TV, Roku, Apple TV, and Samsung Smart TV CTV apps.

The series of reports provide a detailed analysis of the global status of non-standard and malformed Bundle IDs in the open programmatic advertising supply chain as of Q1 2025. A "malformed" Bundle ID refers to an app identifier used in the ad bid that is either uncorrelated or unmapped to any known app, according to Pixalate’s Bundle ID mapping technology. These "malformed" Bundle IDs disrupt ad targeting and campaign measurement while paving the way for ad fraud.

Key Findings:

Roku

  • 3% of Bundle IDs were malformed, unidentified, and/or fraudulent (~200 out of 6k)
    • 51% of Bundle IDs across Roku traffic used actual App Store IDs, which is the recommended method for app identification according to the IAB Tech Lab

Amazon Fire TV

  • 44% of Bundle IDs were malformed, unidentified, and/or fraudulent (~2k out of 4.4k)
    • 39% of Bundle IDs across Amazon Fire TV traffic used actual App Store IDs, which is the recommended method for app identification according to the IAB Tech Lab

Apple TV

  • 57% of Bundle IDs were malformed, unidentified, and/or fraudulent (~1k out of 1.9k)
    • 33% of Bundle IDs across Apple TV traffic used actual App Store IDs, which is the recommended method for app identification according to the IAB Tech Lab

Samsung Smart TV

  • 26% of Bundle IDs were malformed, unidentified, and/or fraudulent (~500 out of 1.9k)
    • 57% of Bundle IDs across Samsung Smart TV traffic used actual App Store IDs, which is the recommended method for app identification according to the IAB Tech Lab

Top Malformed, Unidentified and/or Fraudulent Bundle IDs (by impression volume) as determined by Pixalate

Rank
(by Impression SOV)
Roku Amazon Fire TV Samsung Smart TV Apple TV
1 eyeq eyeq eyeq eyeq
2 indicue indicue scripps com.spectrumreach.tv
3 onefox onefox onefox 711074
4 app.ott.ctv scripps 1233569 indicue
5 scripps 1233569 1116225 app.ott.ctv

 

For this report, Pixalate’s data science and analyst team analyzed over 2 billion open programmatic advertising transactions across more than 14,000 CTV Bundle IDs linked to over 6,000 unique CTV apps on Roku, Amazon Fire TV, Samsung Smart TV, and Apple TV traffic in March 2025.

Download the complete reports:

Samsung Smart TV     Amazon Fire TV

Apple TV     Roku

About Pixalate

Pixalate is a global market-leading ad fraud protection, privacy, and compliance analytics platform. Pixalate works 24/7 to guard your reputation and grow your media value by offering the only system of coordinated solutions across display, app, video, and CTV for the detection and elimination of ad fraud. Pixalate is an MRC-accredited service for the detection and filtration of sophisticated invalid traffic (SIVT) across desktop and mobile web, mobile in-app, and CTV advertising. www.pixalate.com

Disclaimer

The content of this press release, and the Malformed Bundle IDs Reports (the “Report”), reflect Pixalate's opinions with respect to factors that Pixalate believes can be useful to the digital media industry. Pixalate's opinions are just that, opinions, which means that they are neither facts nor guarantees. Pixalate is sharing this data not to impugn the standing or reputation of any entity, person or app, but, instead, to report findings and trends pertaining to programmatic advertising activity across CTV in the time period studied. Per the MRC, “'Fraud' is not intended to represent fraud as defined in various laws, statutes and ordinances or as conventionally used in U.S. Court or other legal proceedings, but rather a custom definition strictly for advertising measurement purposes. Also per the MRC, “‘Invalid Traffic’ is defined generally as traffic that does not meet certain ad serving quality or completeness criteria, or otherwise does not represent legitimate ad traffic that should be included in measurement counts. Among the reasons why ad traffic may be deemed invalid is it is a result of non-human traffic (spiders, bots, etc.), or activity designed to produce fraudulent traffic.”.

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