---
title: Pixalate's April 2026 Most Common Mobile App Ad Fraud Types
description: Pixalate's April 2026 Most Common Mobile App Ad Fraud Types on the Google Play Store and Apple App Store
image: https://www.pixalate.com/hubfs/Blog%20Media/2026%20Covers%20and%20Images/MONTHLY%20TOP%20MOBILE%20AD%20FRAUD%20TYPES%20GOOGLE%20-%20APPLE%20BLOG%20COVER.jpg
---

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 2 min read

# Pixalate Releases April 2026 Most Common Mobile App Ad Fraud Types: ‘High Risk Device ID’ Most Common Type Across Google Play Store (28%); ‘High Risk IP’ Most Common on Apple App Store (23%)

 Written by [Pixalate](https://www.pixalate.com/blog/author/pixalate)

 May 18, 2026 9:00:00 AM

*According to Pixalate research, ‘Device ID Stuffing’ came at second on Google Play Store for the highest fraud Share of Voice (SOV) while ‘Publisher Fraud’ was at the second spot on Apple App Store*

**LONDON, May 15, 2026 --** [Pixalate](https://www.pixalate.com), an ad fraud and privacy compliance platform, today released the April 2026 Most Common Mobile Ad Fraud Types Report. The report examines the most common types of invalid traffic among mobile apps globally on the [Google Play Store](https://www.pixalate.com/pixalates-monthly-top-google-play-store-ad-fraud-types) and [Apple App Store](https://www.pixalate.com/pixalates-monthly-top-apple-app-store-ad-fraud-types). Regional insights are available for Europe, the Middle East and Africa (EMEA), Asia-Pacific (APAC), Latin America (LATAM), and North America.

Pixalate’s data science team analyzed over 25 billion+ open programmatic advertising impressions on 688K+ mobile apps in April 2026.

## **Top 5 Mobile App Ad Fraud Types- Google Play Store**

| **Rank** | **Region** | **Fraud Type** | **Fraud Share of Voice (SOV) - April 2026** |
| --- | --- | --- | --- |
| 1 | GLOBAL | High Risk Device ID | **28%** |
| 2 | GLOBAL | Device ID Stuffing | **13%** |
| 3 | GLOBAL | Masked IP | **12%** |
| 4 | GLOBAL | High Risk IP | **10%** |
| 5 | GLOBAL | Display Impression Fraud | **10%** |

 

## **Top 5 Mobile App Ad Fraud Types-Apple App Store **

| **Rank** | **Region** | **Fraud Type** | **Fraud Share of Voice (SOV) - April 2026** |
| --- | --- | --- | --- |
| 1 | GLOBAL | High Risk IP | **23%** |
| 2 | GLOBAL | Publisher Fraud | **19%** |
| 3 | GLOBAL | Masked IP | **15%** |
| 4 | GLOBAL | High Risk Device ID | **11%** |
| 5 | GLOBAL | Display Impression Fraud | **7%** |

 

**Download the April 2026 IVT Types:**

[![Google Play Store](https://no-cache.hubspot.com/cta/default/2364596/68fae2ad-2897-44ec-9cb0-2d47d464a1f0.png)](https://cta-redirect.hubspot.com/cta/redirect/2364596/68fae2ad-2897-44ec-9cb0-2d47d464a1f0)     [![Apple App Store](https://no-cache.hubspot.com/cta/default/2364596/0e108004-a92d-40e3-ba54-97959a5372e6.png)](https://cta-redirect.hubspot.com/cta/redirect/2364596/0e108004-a92d-40e3-ba54-97959a5372e6)

 

**About Pixalate**

Pixalate is a global platform specializing in privacy compliance, ad fraud prevention, and digital ad supply chain data intelligence. Founded in 2012, Pixalate is trusted by regulators, data researchers, advertisers, publishers, ad tech platforms, and financial analysts across the Connected TV (CTV), mobile app, and website ecosystems. Pixalate is accredited by the MRC for the detection and filtration of Sophisticated Invalid Traffic (SIVT).  [pixalate.com](https://www.pixalate.com/)

**Disclaimer**

*The content of this press release, and the April 2026 Most Common Mobile App Ad Fraud Types Reports (the "Reports"), **reflects Pixalate's opinions with respect to factors that Pixalate believes may be useful to the digital media industry. **Any data shared is grounded in Pixalate’s proprietary technology and analytics, which Pixalate is continuously evaluating and updating. Any references to outside sources should not be construed as endorsements. **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 in the time period studied. **Per the Media Rating Council (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.” Where the traffic characteristics are suggestive of deliberate intent to mislead, such IVT is often referred to as “ad fraud.” Also 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.”*

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[![](https://www.pixalate.com/hubfs/Blog%20Media/2026%20Covers%20and%20Images/MONTHLY%20MOST%20COMMON%20MOBILE%20AD%20FRAUD%20TYPES%20GOOGLE%20-%20APPLE%20BLOG%20COVER.png) ](https://www.pixalate.com/blog/pixalates-may-2026-most-common-mobile-app-ad-fraud-types)

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# Disclaimer

 Disclaimer: The content of this page reflects Pixalate’s opinions with respect to the factors that Pixalate believes can be useful to the digital media industry. Any proprietary data shared is grounded in Pixalate’s proprietary technology and analytics, which Pixalate is continuously evaluating and updating. Any references to outside sources should not be construed as endorsements. Pixalate’s opinions are just that - opinion, not facts or guarantees.

 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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