"Apple utilizes both human review and advanced technology to identify and stop the use of stolen financial information," the tech giant said, summing up the approach behind a surge of enforcement numbers the company published for 2025.
Apple's fraud-prevention totals, 2019–2025
Apple said it blocked more than $11 billion in fraudulent App Store transactions over the last six years, including more than $2.2 billion in potentially fraudulent transactions in 2025 alone. The company reported blocking more than 1.1 billion fraudulent account creations in 2025 and deactivating 40.4 million customer accounts suspected of fraud and abuse during the same period.
Apple also reported that it terminated 193,000 developer accounts for fraud concerns and rejected over 138,000 developer enrollments. Last year the company stopped more than 5.4 million stolen credit cards from being used and banned nearly 2 million user accounts.
Those 2025 figures represent an increase from 2024, when Apple said it blocked over $2 billion in potentially fraudulent transactions, identified nearly 4.7 million stolen credit cards, and blocked over 1.6 million accounts from making further transactions.
App Review and developer enforcement in 2025
Apple's App Review team evaluated over 9.1 million app submissions in 2025, up from 7.7 million the prior year. From that volume the company rejected more than 443,000 submissions for privacy violations, over 371,000 for being copycats or misleading apps, and more than 22,000 for containing hidden or undocumented features.
The company removed nearly 59,000 apps for bait-and-switch tactics in 2025—almost triple the 17,000 removed for the same reason in 2024—while also terminating and refusing developer access as noted above. Those actions highlight the App Store's enforcement at the developer-onboarding and storefront levels.
Discovery fraud, ratings, and search manipulation
Apple said it processed more than 1.3 billion ratings and reviews in 2025 and blocked nearly 195 million fraudulent app reviews and ratings. On the discovery front, the company prevented nearly 7,800 deceptive apps from appearing in search results and blocked 11,500 from App Store charts. Apple further detected and blocked 28,000 illegitimate apps on pirate storefronts.
All of this work runs against a backdrop the company described as large: the App Store draws over 850 million weekly visitors across 175 storefronts worldwide, a scale that makes discovery integrity and rating quality high-impact problems when manipulation occurs.
Machine learning and human review at scale
Apple described its enforcement as a blend of manual and automated methods: "By leveraging machine learning, Apple teams build powerful models to accelerate fraud detection and quickly evaluate new deceptive tactics. These technologies also provide a comprehensive view of fraudulent activity across customer accounts, devices, and payment methods," the company said.
That combination of machine learning and human review underpins the firm's reported ability to stop stolen payment instruments, flag suspect developer enrollments, and block fraudulent account creation at massive scale.
What this means for technologists, developers, and end users
- Technologists and security teams: The report emphasizes machine learning models and cross-signal analysis across accounts, devices, and payment methods—signals these teams will watch for integration or monitoring when assessing fraud controls.
- Developers and app publishers: Apple’s figures—193,000 developer account terminations and 138,000 rejected enrollments—underscore the operational risk of policy and fraud violations during onboarding and post-publication review.
- End users and consumers: With Apple stopping more than 5.4 million stolen credit cards and deactivating 40.4 million suspect accounts in 2025, the company points users who see suspicious activity to reportaproblem.apple.com for follow-up.
Apple's published totals show a year-to-year increase in the volume and value of blocks, rejections, and account actions. The company frames those results as the product of machine learning plus human review and invites users to report suspicious activity directly. Whether the upward trend in enforcement and blocked value continues will be an outcome to watch as Apple publishes future tallies.
