How This Briefing Works
This report opens with key findings, then maps the gaps between what AppsFlyer discloses and what BLACKOUT observed at runtime. From there: what it means for your organization, what to do about it, and the detection data and evidence underneath.
Key Findings
Analysis pending. Findings will appear here once intelligence collection is complete.
Claims vs. Observed Behavior
design_concern
“Privacy-preserving SDK methods available”
Privacy controls exist but user-level data sharing is ON by default; effectiveness depends on advertiser implementation, not platform defaults
pending_verification
“Not a data broker or ad network”
AppsFlyer states it does not sell user data, but cross-device matching using Platform Data aggregated across 15,000+ customers creates identity assets; Signal Hub data collaboration features blur the line between processor and platform
pending_verification
“Fingerprinting-adjacent methods acceptable if output matches SKAdNetwork granularity”
This interpretation of Apple privacy policy is self-serving and not confirmed by Apple; runtime SDK data collection behavior not yet verified via scanner
pending
“Awaiting full scanner observation”
Analysis based on public documentation, SDK documentation, privacy policies, and product announcements. Runtime behavior of SDK, actual data collection scope, and postback contents require direct observation.
What This Means For You
What To Do About It
Role-specific actions based on observed behavior
Recommended Actions for AppsFlyer
- →- Immediately audit your AppsFlyer partner integration configurations and implement setSharingFilterForPartners to restrict default user-level data sharing with ad networks that do not require it. - Review AppsFlyer's use of Platform Data (cross-device matching) and assess whether your privacy policy and user consent mechanisms adequately disclose this data processing. - Evaluate the Aggregated Advanced Privacy (AAP) framework and enable it for all partner integrations where user-level postbacks are not operationally required. - Assess the scope of data flowing into AppsFlyer's Signal Hub and data collaboration features, and determine whether these new capabilities introduce data sharing beyond your original measurement agreement. - Request written confirmation from AppsFlyer regarding their fingerprinting practices on iOS and whether any data collection methods in the SDK would be considered tracking under Apple's ATT framework.
Negotiation Leverage
- →Leverage Points: While AppsFlyer is the market leader, the MMP market includes strong alternatives (Adjust, Singular, Kochava, Branch) that create credible switching options. AppsFlyer's expansion into AI and data collaboration creates new revenue streams that depend on customer data volume, giving them incentive to retain large customers. The fingerprinting controversy creates reputational sensitivity that makes AppsFlyer responsive to privacy-focused contractual demands.
- →Key Questions: (1) Why is user-level data sharing with partners enabled by default rather than requiring opt-in? (2) What data from our SDK deployment is used as Platform Data for cross-device matching, and is this data aggregated with data from other AppsFlyer customers? (3) Does Signal Hub or any data collaboration feature use our data to benefit other brands or partners? (4) What specific data collection methods does the SDK use on iOS, and do any of these methods constitute fingerprinting under Apple's definition? (5) Can you contractually guarantee that our data is processed only for our measurement purposes and not used for platform-level products?
- →Contract Protections: Negotiate default-off data sharing configuration as a contractual requirement. Require explicit consent before any data is used for Platform Data, cross-device matching, or data collaboration features. Include audit rights covering data sharing with all integrated partners. Add contractual definition of fingerprinting aligned with Apple's ATT framework and require compliance. Negotiate data isolation provisions ensuring your data is not aggregated with other customers for platform-level products.
IOC Manifest
Indicators of compromise across 4 categories. Use for detection rules, CSP policies, or Pi-hole blocklists.
Ecosystem & Supply Chain
Evidence Artifacts
Artifacts collected during analysis, available with evidence-tier access.
Complete network capture with all requests and responses
164 detection signatures across scripts, domains, cookies, and network endpoints