CVE-2026-47364 in Android App
Summary
by MITRE • 08/07/2026
On every successful login, the Datadog Android application calls FirebaseCrashlytics.setUserId with the signed-in user's Datadog UUID — a stable per-user identifier that is meaningful inside Datadog. This associates the Datadog user UUID with the device's Firebase installation ID on Google's backend. Separately, uncaught exceptions are forwarded to Firebase Crashlytics via recordException, attaching stack traces (which may include internal class names, package names, in-flight data referenced by crash frames, and any breadcrumbs) to the same user UUID. No visible consent gate or opt-out for Crashlytics tagging was identified in the reviewed code paths. No email, name, or organization data is forwarded to Crashlytics in the reviewed paths.
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Analysis
by VulDB Data Team • 08/07/2026
The Datadog Android application demonstrates a significant privacy and security concern through its automatic integration with Firebase Crashlytics without explicit user consent or opt-out mechanisms. This vulnerability stems from the application's design pattern where every successful login triggers FirebaseCrashlytics.setUserId with the Datadog UUID, creating a persistent user identifier that links device-specific crash reporting data to individual user accounts. The technical flaw represents a violation of privacy by default behavior, as it automatically establishes cross-platform tracking between the Datadog user identity system and Google's Firebase infrastructure without any visible user consent mechanisms.
The operational impact of this implementation extends beyond simple crash reporting capabilities into serious data exposure risks. When uncaught exceptions are forwarded to Firebase Crashlytics via recordException calls, the system attaches detailed stack traces that can include internal class names, package names, in-flight data referenced by crash frames, and breadcrumb information - all of which may contain sensitive operational details about the application's behavior and underlying systems. This creates a scenario where user-specific crash data becomes permanently associated with the device's Firebase installation ID, potentially enabling long-term tracking of individual users across different sessions and applications.
This vulnerability aligns with CWE-506 (Embedded Malware) and CWE-359 (Exposure of Private Personal Information) while also demonstrating characteristics consistent with ATT&CK technique T1566 (Phishing) through the lack of explicit consent mechanisms. The absence of visible consent gates or opt-out options in the reviewed code paths creates a situation where users unknowingly participate in data collection processes that could expose their operational patterns and potentially sensitive information. The implementation fails to adhere to privacy by design principles and lacks proper user control over data sharing with third-party services, particularly concerning the automatic association of stable user identifiers with crash reporting mechanisms.
The security implications of this design pattern are substantial, as it creates a persistent tracking mechanism that can be exploited for user profiling and behavioral analysis. The combination of user UUID association with Firebase installation IDs enables sophisticated tracking capabilities that extend beyond the intended scope of crash reporting. This implementation pattern violates fundamental privacy principles by automatically collecting and transmitting data without explicit user awareness or consent, potentially exposing users to risks from data breaches or unauthorized access to their crash reporting information. Organizations deploying this application face potential compliance issues with privacy regulations such as GDPR, CCPA, and other data protection frameworks that require explicit consent for data processing activities involving personal identifiers.
Recommended mitigations include implementing explicit user consent mechanisms before enabling Firebase Crashlytics integration, providing clear opt-out options for crash reporting features, and ensuring that only minimal necessary data is transmitted to third-party services. The application should also implement proper data anonymization techniques where possible, and organizations should conduct comprehensive privacy impact assessments to understand the full scope of data exposure created by this automatic integration pattern.