An AI image app is ready for Apple review only when it operates as a complete, enforceable service—not merely as a prompt box connected to an image model. Before submission, implement pre- and post-generation safety filters, reporting and blocking tools, privacy and deletion controls, Apple-compliant login and payments, accurate age and intellectual-property disclosures, and a reproducible review path with live services and test credentials.
Apple’s Guideline 1.2 expressly covers “AI content creation apps.” In October 2026, Apple also clarified that nonconsensual intimate imagery, including imagery generated with AI tools, must be proactively prevented and removed. The controls below are therefore product requirements, not text to place only in a policy page.
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What Apple will evaluate in an AI image app
App Review evaluates the user experience, the services behind it, the data flows, and the developer’s ability to control abuse. A successful submission lets a reviewer create an image, encounter the same safeguards as an ordinary user, understand what data leaves the device, test account and purchase functions, and reach support or deletion controls without assistance from the developer.
Guideline 1.2 applies to social products, user-generated-content platforms, and AI content-creation apps. Its practical requirements include filtering objectionable material, allowing users to report problems, responding in a timely way, blocking abusive users where interaction exists, and publishing usable contact information. Apple’s October 2026 clarification adds a specific obligation to prevent and remove nonconsensual intimate imagery, including synthetic images made by the app.
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Apple does not publish a universal approval percentage or a required number of moderation employees. You must be able to demonstrate that your controls work, that an incident has an owner, and that violating material can be taken down.
Design a moderation system that works before and after generation
Write an enforceable content policy
Start with a decision table that every product, moderation, and support team can use. Separate content into at least three outcomes: allowed, blocked, and escalated for human review. Include sexual exploitation, child sexual abuse material, nonconsensual intimate imagery, sexualized depictions of real people without permission, threats, bullying, impersonation, harassment, extremist or criminal instructions, and other categories prohibited by Apple’s current safety rules.
Define the policy for both text prompts and image inputs. A reference-photo feature can create the same risks as a text-only generator, and a harmless prompt can become unsafe when combined with an uploaded face or an image-editing instruction. Record which rule fired, what action was taken, and whether a moderator overrode the decision.
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Filter prompts and uploaded images before a request reaches the model
- Normalize the request. Detect obfuscation, alternate spellings, encoded text, and prompt-injection attempts before classification.
- Classify text and images. Run the prompt, reference image, and relevant metadata through safety classifiers. Treat uncertain or high-risk results as blocked or escalated rather than silently passing them to the generator.
- Apply user and account controls. Check prior violations, age eligibility, rate limits, and any active suspension before starting a generation job.
- Return a useful refusal. Explain that the request cannot be completed and offer a safe alternative. Do not reveal classifier thresholds or internal evasion signals.
- Log the decision. Store the minimum event data needed for investigation under the retention period disclosed to users.
Do not rely on a single keyword list. A layered approach can combine classifiers, rules, rate limits, account history, and a human escalation queue. Apple’s requirement is an operational mechanism, so a static “users must behave responsibly” disclaimer is not a substitute.
Inspect every generated output
Run an output check before an image is displayed, downloaded, or shared. Scan for prohibited sexual content, exploitation, nonconsensual intimate imagery, graphic violence, hateful or abusive material, and unsafe transformations of real people. If the output fails, discard or quarantine it, show a neutral failure message, and prevent retries from bypassing the same control.
Keep moderation state with the asset. An image that was safe in a private draft may become unsafe after an edit, an upscaling pass, or a face swap. Re-scan after every transformation and before public or peer-to-peer sharing.
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Provide reporting, blocking, and removal tools
Place a visible report action beside shared images, user profiles, comments, and other user-controlled content. Ask for a category and optional explanation, then issue a confirmation that does not expose the reporter’s identity. If users can interact with one another, provide a block function that stops the blocked account from contacting or targeting the blocker.
Route reports into a queue with severity, timestamp, asset identifier, account identifier, and decision history. Define an internal response target; Apple requires timely responses but does not publish one universal numeric deadline. High-severity reports, including suspected exploitation or nonconsensual intimate imagery, should bypass ordinary queues for immediate containment, removal, and specialist escalation.
Give moderators the ability to hide an image, remove it permanently, suspend or terminate an account, invalidate shared links, and preserve evidence needed for an appeal or legal request. Publish a support address or in-app contact route that is monitored by a real team.
Prevent and remove nonconsensual intimate imagery
Do not permit prompts or uploads that sexualize a real person without documented authorization. Add detection for nudity, sexual context, face matching, and requests to undress or fabricate intimate scenes. Apply the controls to generation, editing, variation, inpainting, and image-to-image workflows.
When a report arrives, immediately restrict access while the case is reviewed. Remove confirmed material from feeds, caches, thumbnails, search indexes, and shared links; record the action; and prevent the same file or near-duplicate from being re-uploaded. Tell the affected user how to report and what response to expect without requiring them to redistribute the image.
Set age and content controls from the actual product risk
Select the App Store age rating based on the content the service can produce, not on the safest marketing example. If generated material can exceed the declared rating, add an age restriction mechanism appropriate to the product and the jurisdictions in which it operates. A “for entertainment only” notice does not authorize prohibited sexual, exploitative, or abusive uses.
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Keep age-related decisions auditable: record the declared or verified age signal, the policy version used, and the reason access was granted or denied. Do not collect more identity information than the age-control design requires.
Make privacy claims match the real AI data flow
Inventory every data item
Create a data map before completing App Store privacy questions. Include prompts, uploaded reference photographs, generated images, face or biometric-like inputs, account and profile identifiers, device identifiers, crash logs, analytics events, advertising identifiers, payment records, moderation reports, support messages, and authentication tokens.
| Data category | Questions your documentation must answer | Controls to verify |
|---|---|---|
| Prompts and source images | Which model or cloud service receives them, for what purpose, in which region, and for how long? | Transport encryption, access restrictions, deletion job, model-training opt-out or disclosure where applicable |
| Generated images | Are they private, shared, or public by default? Who can access copies and thumbnails? | Access control, sharing revocation, moderation state, removal from caches and backups according to policy |
| Account and device identifiers | Why are they collected, which vendors receive them, and when are they deleted? | Data-minimization review, retention schedule, account-deletion cascade |
| Analytics and advertising data | Does any SDK track users across companies’ apps or websites? | Consent flow, App Tracking Transparency authorization where required, accurate privacy answers |
| Moderation and support records | Who can see reports, how long are records retained, and how are legal holds handled? | Role-based access, audit log, documented lawful-retention exception |
Your privacy policy must state where each category goes, why it is used, retention duration, deletion behavior, and every third party that receives it. Put the policy both in App Store Connect metadata and inside the app. The in-app version should be reachable before or during account creation, not hidden behind a support ticket.
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If a service or SDK tracks a user across other companies’ apps or websites, request App Tracking Transparency authorization with the required usage-description key before tracking begins. Explain the purpose in plain language and do not use a preselected or misleading consent control.
Review every third-party SDK for required-reason APIs and data collection. Include its current PrivacyInfo.xcprivacy manifest, validate the combined manifests in the archive, and ensure App Store privacy answers describe the actual combined behavior. A privacy label that omits data sent to an AI provider or analytics service creates a review discrepancy even if the SDK itself is reputable.
Control retention and deletion in the backend
Deletion must reach the systems that handle generation jobs, source files, outputs, moderation records, analytics identifiers, and vendor copies. Distinguish data that is deleted immediately from data retained for a stated legal or security reason. Document backup expiration and cached derivatives so support staff can give an accurate answer instead of promising instant erasure that the architecture cannot deliver.
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Handle accounts, login, and in-app deletion
If the app supports account creation, Apple requires users to initiate deletion inside the app. Apple gives June 30, 2022 as the effective date for this requirement. A web form, an email request, or an instruction to contact support is not an equivalent path.
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- Explain the consequences. State what happens to prompts, source photos, generated images, shared content, subscriptions, credits, reports, and any data retained by law.
- Confirm deliberately. Require a confirmation step that prevents accidental deletion without turning the process into a support conversation.
- Execute the cascade. Revoke sessions and tokens, remove or anonymize associated data, withdraw shared images, cancel future processing, and send deletion requests to disclosed processors.
- Show completion. Give the user a clear result and a support route for residual lawful-retention questions.
If users can sign in with a third-party social identity provider for the primary account, provide an equivalent privacy-preserving sign-in option that meets Apple’s requirements. Sign in with Apple is the obvious implementation to evaluate, but the exact choice depends on which providers your app offers and how account linking works. Test first login, returning login, revoked credentials, email relay addresses, and account deletion together.
Let users explore useful functionality before forcing registration where practical. If generation, saving, or sharing genuinely requires an account, explain that requirement at the point it becomes necessary rather than showing an unexplained login wall on first launch.
Use Apple’s payment rules for digital generation features
Credits, subscriptions, premium models, styles, image limits, upscaling, editing tools, and other digital features unlocked inside the app generally belong in Apple’s in-app purchase system. Configure each product in App Store Connect, connect it to the production entitlement service, and make the purchase flow functional in the submitted build.
Make products reviewable
- Use product names and descriptions that match the actual entitlement.
- Show price, billing period, renewal terms, and any one-time credit allowance accurately for the reviewer’s storefront.
- Provide a restore-purchases action where applicable and explain cancellation through the user’s Apple account settings.
- Ensure failed, pending, refunded, and restored transactions produce the correct entitlement state.
- Do not advertise a feature in screenshots or metadata that is unavailable after purchase or disabled in the review environment.
In Review Notes, tell Apple exactly where to reach the paywall, which product to select, how a test purchase behaves, and how premium generation is recognized by the backend. Keep entitlement checks observable in server logs without exposing payment credentials.
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Protect intellectual-property and likeness rights
Do not imply that users may freely generate protected characters, celebrity likenesses, logos, or copyrighted styles. The developer remains responsible for legal compliance and authorization. Explain restrictions in the prompt experience, block clearly infringing requests where your policy requires it, and provide a reporting route for rights holders.
Maintain records for licenses and permissions covering training inputs, third-party assets, reference images, and commercial outputs where relevant. If the product accepts a user-uploaded photograph, require the user to confirm they have the necessary rights and provide a removal process for unauthorized material. Avoid marketing language that promises ownership or unrestricted commercial use unless your contracts and local law support that promise.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Prepare the App Review submission package
Review access is part of compliance. Apple’s guidance asks developers to provide App Review with full access to the app. Submit a stable final build, keep the backend and model services live, and remove placeholder screens or disabled paths.
- Provide working credentials. Include a demo account, password or one-time-code instructions, and any second-factor details. If account creation is required, explain how a reviewer can complete it without a real personal identity.
- Expose every important path. Describe generation, image upload, editing, sharing, reporting, blocking, account deletion, subscription restoration, and support contact locations.
- Document the generation pipeline. Name the categories of external AI services used, what data each receives, whether data is retained, and which safeguards run before and after generation.
- Supply moderation test cases. Give safe prompts that demonstrate ordinary generation and controlled prompts that trigger refusal, escalation, reporting, or removal. Do not ask a reviewer to create illegal material.
- Explain payment access. Identify products, storefront assumptions, test-purchase instructions, entitlement timing, and restoration behavior.
- Describe non-obvious behavior. Explain asynchronous jobs, region restrictions, age gates, invite-only sharing, image expiration, and any feature that looks broken without context.
- Keep regulated documentation ready. If the app touches a regulated field or requires special authorization, attach the relevant documentation through the submission process.
Use Review Notes as an operating manual, not a marketing paragraph. A reviewer should be able to follow the same sequence every time and reach a meaningful result even if a third-party model briefly fails. Monitor credentials and revoke them after review if they expose production data.
Choose architecture and service providers against Apple’s actual risks
Whether you host models yourself or use external AI and moderation services, evaluate the implementation against the following criteria. Apple does not approve a vendor by name; it evaluates the behavior you ship and the disclosures you make.
| Decision area | Questions to answer before submission | Evidence to keep |
|---|---|---|
| Moderation coverage | Are prompts, uploads, outputs, edits, and shared images all checked? | Policy version, classifier results, refusal tests, removal records |
| False positives and escalation | Can a legitimate user appeal, and can a moderator override a decision safely? | Queue workflow, reviewer roles, appeal outcomes, audit trail |
| Retention and deletion | Can you delete source files and outputs from every processor and cache? | Processor terms, deletion requests, job logs, backup-retention statement |
| Regional processing | Where are prompts and images processed, and does the privacy policy say so? | Data-flow diagram, subprocessors, transfer safeguards |
| Account controls | Do login, blocking, suspension, and in-app deletion work end to end? | Test accounts, deletion results, revoked-session tests |
| Review reproducibility | Can Apple reach the same generation, safety, and purchase states using your instructions? | Demo credentials, deterministic test cases, Review Notes |
| Payment observability | Can you show entitlement changes for purchase, renewal, refund, and restore? | Transaction logs, server notifications, entitlement test results |
| Age controls | Does access change when a user is below the product’s declared threshold? | Age-policy decision, test results, user-facing explanation |
| Incident response | Who can remove content, suspend an account, notify users, and preserve evidence? | On-call ownership, severity matrix, response records |
For any vendor or SDK, verify contract terms, model-training settings, regional availability, incident notification, and deletion guarantees. If a provider cannot explain where a prompt goes or how it is removed, do not describe that flow as private or deleted.
Run a pre-submission compliance test
Use a clean device and a fresh account, then repeat the test with a returning account. Record screenshots and backend event IDs so a failed path can be reproduced.
Quick Recap
- Generate an ordinary image with no account, if guest exploration is supported.
- Create an account and confirm the privacy policy is reachable at the point of collection.
- Submit blocked prompts and unsafe reference images; verify refusal, logging, and no output exposure.
- Generate an image, edit it, upscale it, and share it; confirm each stage is rechecked.
- Report an image, block another user, and verify the expected visibility and contact restrictions.
- Complete account deletion and confirm sessions, images, prompts, and shared links follow the documented outcome.
- Authorize or deny tracking permission and inspect analytics behavior in both states.
- Buy, restore, refund, and expire a digital entitlement in the review environment.
- Disconnect the model provider or force a timeout; confirm the app fails safely without charging for an unfulfilled generation.
- Open support contact information and verify that a real team receives the message.
Common rejection risks and precise fixes
| What Apple may observe | Why it is risky | Fix before resubmitting |
|---|---|---|
| A policy page says abuse is forbidden, but there is no report or removal control. | Guideline 1.2 requires mechanisms, not disclosure alone. | Add in-app reporting, moderation queues, blocking where applicable, escalation ownership, and documented removal actions. |
| A generated intimate image remains available after a report. | Apple now explicitly includes AI-generated nonconsensual intimate imagery in proactive prevention and removal requirements. | Quarantine reported content immediately, investigate, remove confirmed copies and links, and prevent re-upload. |
| The privacy label omits prompts sent to an external model. | App Store answers do not match the actual data flow. | Update the inventory, policy, consent UI, SDK manifests, and privacy answers together. |
| Account deletion opens a website or email composer. | Apps supporting account creation must let users initiate deletion inside the app. | Place a working Delete Account control in settings and execute the backend cascade. |
| A social login is offered without an equivalent privacy-preserving option. | Login choices may not satisfy Apple’s sign-in requirements. | Evaluate Sign in with Apple or another qualifying equivalent and test linking and deletion. |
| A premium model works only after an undocumented server flag is enabled. | Reviewers cannot verify the advertised digital feature or entitlement. | Configure the product, make it reachable in the submitted build, and describe the path in Review Notes. |
| Demo credentials expire or the model endpoint is offline. | Apple cannot review the core functionality. | Keep credentials, backend services, and required purchase access live throughout review. |
| Marketing promises unrestricted celebrity or copyrighted-style generation. | The claim may conflict with rights and authorization obligations. | Revise metadata, add rights controls, and document permissions and takedown handling. |
Final submission checklist
- Content categories are documented as allowed, blocked, or escalated.
- Prompt, upload, output, edit, and sharing paths have enforceable safety checks.
- Reporting, blocking, account suspension, removal, support contact, and audit logs work in production.
- Nonconsensual intimate imagery is proactively blocked and can be removed from every distribution path.
- Age rating and age controls reflect the app’s actual generation capabilities.
- Privacy policy, consent screens, App Store privacy answers, and
PrivacyInfo.xcprivacymanifests agree. - Retention, deletion, subprocessors, regional processing, and model-training use are documented accurately.
- In-app account deletion removes or anonymizes associated data, shared images, and sessions as promised.
- Login options meet Apple’s requirements and survive revoked credentials and account deletion.
- Digital credits, subscriptions, styles, and editing features use correctly configured in-app purchases.
- Rights, likeness, licensing, and takedown responsibilities are addressed in product behavior and metadata.
- Review Notes contain working credentials, test paths, service disclosures, moderation cases, and purchase instructions.
- The submitted build is stable, has no placeholder screens, and connects to live model and moderation services.
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