Over 400 AI Apps Disguised as Pet Portrait Generators Hide Sexually Abusive Deepfake Features

Massive Network of Deceptive AI Apps Uncovered

A WIRED investigation has exposed a sophisticated network of over 400 AI apps and connected domains that disguise sexually abusive deepfake features behind seemingly innocent functionality.1

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Apps like Viefur, which claims to transform pet photos into anthropomorphic portraits for around $4 (130 digital coins), actually serve as cover for generating AI-generated nonconsensual intimate imagery. When accessed under specific conditions, these AI-powered apps stealthily load web interfaces enabling the creation of explicit sexual images and videos using photos users upload.2

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The network includes apps marketed as everyday services—language tutors, AI workout coaches, and pet portrait generators—that conceal deeply troubling capabilities. These sexually abusive AI deepfake tools offer disturbing templates including "bedroom rape" and "threatening knife" scenarios where men hold weapons to women's necks.1

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This represents a systematic exploitation of platform policies designed to protect users from harmful AI-generated content.

How Hidden Deepfake Features Evade Detection

Researchers discovered the deceptive practices after investigating thousands of video ads containing explicit deepfake content published on Facebook and Instagram. These Meta ads reached tens of thousands of people and linked directly to apps in the Apple App Store and Google Play Store, allowing users to generate explicit images and make payments using Apple Pay and Google Pay.1

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The apps employ sophisticated bait-and-switch tactics to pass app store reviews. Paul Bouchaud, lead researcher at nonprofit AI Forensics who reverse-engineered code, explains: "Each time the application is downloaded, there is a call to the server with some information, such as where the user is coming from, the language, some unique identifier, and then the server replies whether or not to show the explicit or the non-explicit version."1

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One apparent trigger is downloading the app after clicking an associated ad on Meta's platforms.2

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These server-side triggers allow developers to show benign content during initial reviews while activating hidden features for specific users afterward. Websites linked to the apps appear completely black with URLs updating to include the word "risk," but they host the explicit deepfake layer loaded within each app.1

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Scale and Organization Behind the AI Misuse

The network appears to be "an organized, commercially run operation: One operator behind hundreds of disposable apps and domains, cloaked to pass App Store review and pushed through tens of thousands of Meta ads under fake payer names," according to Bouchaud.1

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Researchers traced the operation to Chinese developers and a Hong Kong-registered entity called KeLing Technology Limited through web domains and operational patterns.1

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Maël Le Touz, staff threat researcher at security firm Infoblox, found that websites' JavaScript bundles contained "this giant configuration list of other domains with different encryption keys," revealing app package details, Facebook advertising trackers, and the entire network structure.1

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In September 2026, researchers identified 27 related apps on Google Play Store that had collectively accumulated more than 350,000 downloads, with many rated suitable for all age groups.3

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The network has been publishing apps for approximately one year, at times releasing dozens per week, despite Google, Apple, and Meta claiming to enforce policies prohibiting harmful deepfake content.1

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Platform Responses and Systemic Failures

Apple removed 19 apps after WIRED shared investigation details. Spokesperson Adam Dema stated: "We review every app before it's published, and these apps complied with our rules when we reviewed them. After approval, their developers changed the website the app pulls its content from, replacing what we approved with pornographic content."2

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Apple also reported suspending tens of thousands of apps over the previous year for similar deceptive practices.3

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On October 16, Apple updated its guidelines to address these threats. Guideline 1.2 now explicitly prohibits AI-generated nonconsensual intimate imagery, requiring developers to prevent or remove such content. Guideline 2.5.19 clarifies Apple's prohibition against hidden features activated after approval.3

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Meta claims it has taken action against more than 10,000 ad accounts linked to domains associated with these apps.2

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However, these policy updates face fundamental limitations. Developers can change content delivered from external servers without submitting new app versions for approval, allowing prohibited functionality to appear after passing review. This highlights a critical vulnerability in current app store review processes that malicious actors are actively exploiting to distribute sexually abusive content at scale.