Apple Reports Comprehensive Mitigation of Fraudulent Activities within the App Store Ecosystem for 2025.
Apple 發布 2025 年 App Store 生態系統全面緩解詐騙活動報告。
Introduction
Apple has released statistical data detailing its efforts to neutralize fraudulent transactions and malicious software submissions across its global App Store infrastructure during the 2025 calendar year.
Apple 已發布統計數據，詳細說明其在 2025 曆年期間，如何在其全球 App Store 基礎設施中抵禦詐騙交易與惡意軟體提交。
Main Body
The proliferation of generative artificial intelligence and automated bot networks has precipitated a surge in sophisticated adversarial tactics. Apple reports that these technologies are being leveraged to manipulate application rankings, fabricate user reviews, and facilitate the creation of fraudulent accounts. Consequently, the organization observed a substantial increase in app submissions, totaling over 9.1 million reviews, necessitated by the lowered barrier to entry for software development provided by AI coding tools.
生成式人工智慧與自動化機器人網路的普及，導致複雜的對抗策略激增。Apple 報告指出，這些技術被用於操縱應用程式排名、偽造使用者評論以及協助建立詐騙帳號。因此，由於 AI 程式碼工具降低了軟體開發的門檻，該機構觀察到應用程式提交量大幅增加，審查總數超過 910 萬件。
Institutional countermeasures have focused on a hybrid methodology combining machine learning algorithms with human oversight. This strategic alignment enabled the rejection of over 2 million app submissions, including 443,000 for privacy infractions and 371,000 for spam or deceptive practices. Furthermore, the company identified and removed approximately 59,000 'bait-and-switch' applications—software that maintains a benign profile during initial review before transitioning to fraudulent functionality post-approval.
制度性對策集中於一種結合機器學習演算法與人工監督的混合方法。此策略導向使得超過 200 萬件應用程式提交被拒絕，其中包括 44.3 萬件因侵犯隱私，以及 37.1 萬件因垃圾訊息或欺騙行為。此外，該公司識別並移除了約 5.9 萬個「誘騙轉向（bait-and-switch）」應用程式——這類軟體在初次審查期間維持良性面貌，在獲准後才轉換為詐騙功能。
Financial and account-level security measures were equally rigorous. The organization blocked 1.1 billion fraudulent account creation attempts and deactivated 40.4 million existing accounts associated with abuse. In the domain of fiscal security, 5.4 million stolen credit cards were neutralized, and a total of 2.2 billion dollars in potentially fraudulent transactions were obstructed. Additionally, the company mitigated external threats by blocking 28,000 illegitimate apps from pirate storefronts and preventing 2.9 million unauthorized installation attempts in a single month.
財務與帳號層級的安全措施同樣嚴格。該機構封鎖了 11 億次詐騙帳號建立嘗試，並停用了 4,040 萬個與濫用相關的現有帳號。在財務安全領域， neutralized 了 540 萬張盜用信用卡，並攔截了總計 22 億美元的潛在詐騙交易。此外，該公司透過封鎖 2.8 萬個來自盜版商店的非法應用程式，並在單月內防止 290 萬次未經授權的安裝嘗試，以減輕外部威脅。
Regarding platform integrity, Apple processed 1.3 billion ratings and reviews, preemptively blocking 195 million fraudulent entries. The organization also maintained strict adherence to safety standards for minors, rejecting over 5,000 applications from the Kids category. These security imperatives serve as the primary justification for Apple's insistence on maintaining exclusive control over the installation process, despite external regulatory and developer critiques regarding market fairness.
關於平台完整性，Apple 處理了 13 億個評分與評論，預先封鎖了 1.95 億條詐騙條目。該機構亦嚴格遵守未成年人安全標準，拒絕了超過 5,000 個兒童類別的應用程式。儘管外部監管機構與開發者對市場公平性提出批評，但這些安全必要性成為 Apple 堅持維持安裝過程專屬控制權的主要理由。
Conclusion
Apple continues to integrate advanced automated detection systems to counter the evolving complexity of AI-driven fraud and maintain the security of its digital marketplace.
Apple 將持續整合先進的自動化偵測系統，以對抗 AI 驅動詐騙日益增加的複雜性，並維持其數位市場的安全。
Vocabulary Learning
The Architecture of Nominalization and 'Institutional Weight'
To transition from B2 to C2, a student must move beyond describing actions and start describing phenomena. The provided text is a masterclass in Nominalization—the process of turning verbs (actions) and adjectives (qualities) into nouns to create a sense of objectivity, authority, and academic distance.
⚡ The Linguistic Shift: Action Concept
Consider the difference in cognitive load and tone between these two structures:
- B2 Style (Verbal/Active): AI has made it easier for people to code, so more people are submitting apps, which has caused a surge in attacks.
- C2 Style (Nominalized): The lowered barrier to entry for software development provided by AI coding tools... precipitated a surge in sophisticated adversarial tactics.
In the C2 version, the action (lowering the barrier) becomes a noun phrase (the lowered barrier). This allows the writer to treat a complex situation as a single "object" that can then be manipulated by a powerful verb (precipitated).
🔍 Dissecting the "Power Verbs" of C2 Prose
When you nominalize, you cannot use simple verbs like do, make, or get. You require high-precision verbs that describe the relationship between these complex nouns. Note these pairings from the text:
| Nominalized Concept | High-Precision Verb | Effect |
|---|---|---|
| Institutional countermeasures | focused on | Establishes strategic intent |
| Strategic alignment | enabled | Indicates a causal mechanism |
| Security imperatives | serve as | Provides a formal justification |
| External threats | mitigated | Specifies a technical reduction of risk |
🛠️ Advanced Application: The "Conceptual Chain"
C2 mastery involves creating chains of nouns where the end of one phrase triggers the start of the next.
"...the proliferation of generative artificial intelligence... has precipitated a surge in sophisticated adversarial tactics."
The Logic: Proliferation Precipitated Surge Tactics.
By stripping away the "people" (the subjects) and focusing on the "forces" (the nouns), the text achieves a tone of institutional infallibility. To replicate this, stop asking "Who did what?" and start asking "What phenomenon caused what result?"