App Store Policy Sandbox and Entitlement Compliance Risk Matrix
Audit native binary permissions, SDK telemetry, and external linking against app store review guidelines.
Use this template prior to submitting updates or new mobile applications to app store review pipelines. It evaluates SDK compliance, privacy manifests, and entitlement scopes to identify rejection risks.
Role: Mobile Security Auditor & App Store Policy Regulatory Lead
Context
- Binary architecture: {{app_binary_architecture}}
- Requested system entitlements: {{external_entitlements_requested}}
- Third-party SDK inventory: {{third_party_sdk_inventory}}
- Target store jurisdictions: {{target_store_jurisdictions}}
- Telemetry and data collection: {{telemetry_collection_scope}}
- In-app browser and link mechanisms: {{in_app_browser_mechanisms}}
Task
Produce a rigorous App Store guideline compliance and sandboxing risk assessment matrix to evaluate review rejection probabilities and privacy manifest alignment.
Method
- Audit {{app_binary_architecture}} against target store guidelines regarding dynamic code loading, private API calls, and sandboxing.
- Cross-reference {{external_entitlements_requested}} against allowed public entitlements and store justification policies.
- Scrutinize {{third_party_sdk_inventory}} for privacy manifest compliance, required reason APIs, and tracking domain declarations.
- Correlate data transmission from {{telemetry_collection_scope}} with mandatory store privacy nutrition labels across {{target_store_jurisdictions}}.
- Evaluate {{in_app_browser_mechanisms}} against guidelines regarding in-app purchases, external payment links, and account creation.
- Assign risk probability and rejection severity scores (1-5 scale) across all identified compliance vectors.
- Compile an actionable compliance risk mitigation matrix with remediation steps.
Constraints
- MUST cite specific store review guideline sections (e.g., Apple Guideline 2.5.2, Google Play Families Policy).
- MUST classify third-party SDK risks by privacy manifest status and data collection type.
- MUST NOT recommend obfuscation techniques designed to bypass static binary analysis.
- Risk categorization MUST use clear severity tiers: Critical, High, Medium, and Low.
Output format
- Compliance Risk Matrix (columns: Policy Section, Architecture Component, Identified Risk, Severity Tier, Probability Score [1-5], Mandatory Remediation)
- Privacy Manifest & Nutrition Label Mapping Table (SDK/Component vs. Declared Data Category)
- Pre-Submission Review Checklist (4 sequential technical gates)
Self-review
- Ensure all third-party SDKs listed in {{third_party_sdk_inventory}} are evaluated for required reason APIs.
- Verify that risk severities are justified with specific policy citations.
- Confirm that {{external_entitlements_requested}} are validated against standard sandboxing restrictions.
Explicit role, a named task, and discrete steps the model can follow.
Background, inputs and variables the model needs before it starts.
Hard boundaries — what the model must and must not do.
A named, field-level shape for the response.
Ordered work items that force analysis before an answer.
Length and structure that travel across frontier models.
Signal density — instruction weight without padding.
Documented variables so the scaffold adapts to new inputs.
Quality bar, assumptions and behaviour when inputs are thin.
How much real usage the template has behind it.