In the Android AI page, remove or obfuscate the client identifier (cid) from analytics requests. Implement consent gating for analytics before sending any tracking data. Use GA4 with privacy-friendly defaults (anonymize_ip: true, ad_storage/analytics_storage set to 'granted' only after consent). Move to server-side measurement where feasible to avoid exposing user identifiers in URLs. Ensure the data in URLs (dl, dt) does not include PII and that no unique user identifiers are transmitted in query strings.Provide code snippet: 1) Gate GA4 config behind a consent check; 2) Remove cid from URL and rely on cookies; 3) Enable anonymize_ip; 4) If needed, switch to measurement protocol via server-side endpoint.

Audit the Android AI features page to identify which AI/LLM calls are triggered on page load. Move all non-critical calls behind a user consent flow, defer or lazy-load after interaction, and log consent events. Remove default auto-calls if not strictly necessary.

Actionable fix: Implement consent-gated loading for all third-party resources shown in the traffic. 1) Integrate a CMP and guard the following loads behind consent: GTM (id=GTM-KZDPH9F), YouTube iframe API, Google Fonts. 2) For GTM: remove or avoid sending cookieCategory-like parameters; enable IP anonymization; disable advertising features until consent is granted. 3) For YouTube embeds: switch to privacy-enhanced mode using youtube-nocookie.com and only load after consent. 4) For fonts: host locally or ensure loading from fonts.googleapis.com is gated by consent; consider font-display and caching strategies. 5) Add CSP (Content-Security-Policy) to restrict third-party domains until consent and set Referrer-Policy appropriately. 6) Ensure no PII is ever appended to query strings or request bodies in these calls. 7) Provide a minimal, testable patch: wrap script injections with a consent check (e.g., if (userConsentGiven) { loadScript('gtm.js', ...); loadIframe(...); loadFont(...) }