How This Briefing Works
This report opens with key findings, then maps the gaps between what Adjust 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
pending
“Requires claims extraction via CDT”
Live website analysis pending
What This Means For You
What To Do About It
Role-specific actions based on observed behavior
Recommended Actions for Adjust
- →- Audit Adjust SDK data sharing configuration and disable default sharing for all ad network partners not explicitly required for attribution. - Review probabilistic matching settings and evaluate whether fingerprinting-based attribution aligns with your organization's consent architecture and privacy posture. - Request a data processing inventory from Adjust detailing all third-party recipients of device-level data, including AppLovin entities. - Implement server-side attribution validation to cross-reference Adjust's attribution claims against independent conversion data. - Evaluate Adjust's ATT consent rate reporting to understand what percentage of your user base is being attributed through deterministic vs. probabilistic methods.
Negotiation Leverage
- →Leverage: Adjust operates in a competitive MMP market alongside AppsFlyer, Branch, Singular, and Kochava. Switching costs are meaningful but not prohibitive — SDK replacement is a quarterly engineering project, not a multi-year migration. Use competitive pressure to negotiate data minimization terms and restrict default sharing.
- →Key questions for Adjust: (1) What specific data elements are shared with AppLovin entities, and can this be contractually restricted? (2) What percentage of attributions for our app rely on probabilistic matching vs. deterministic identifiers? (3) Can we obtain contractual guarantees that our attribution data is not used to train AppLovin's advertising optimization models? (4) What is the data retention period for device-level event data, and can it be shortened?
- →Contractual protections to seek: Explicit data processing agreement limiting AppLovin cross-entity data use; contractual cap on data retention periods; right to audit third-party data sharing configurations; notification requirements for changes to probabilistic matching methodology; opt-out from any aggregate benchmarking products that incorporate your app's data.
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
375 detection signatures across scripts, domains, cookies, and network endpoints