CVE-2025-48629 in Android
Summary
by MITRE • 12/08/2025
In findAvailRecognizer of VoiceInteractionManagerService.java, there is a possible way to become the default speech recognizer app due to an insecure default value. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.
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Analysis
by VulDB Data Team • 12/21/2025
The vulnerability identified as CVE-2025-48629 resides within the VoiceInteractionManagerService.java component of Android systems, specifically in the findAvailRecognizer method where an insecure default value creates a privilege escalation vector. This flaw represents a critical security weakness that allows malicious applications to potentially assume the role of the default speech recognizer without requiring any additional execution privileges or user interaction. The vulnerability stems from improper initialization or validation of recognizer selection parameters, creating an opportunity for unauthorized apps to hijack speech recognition services that are typically restricted to system-level or trusted applications. Such a flaw directly impacts the Android security model by undermining the principle of least privilege and potentially enabling unauthorized access to sensitive voice data and system controls. The absence of user interaction requirements makes this vulnerability particularly dangerous as it can be exploited automatically without any end-user awareness or consent, representing a significant bypass of Android's security architecture.
The technical implementation of this vulnerability involves the improper handling of default speech recognizer assignments within the Android framework's voice interaction services. When the findAvailRecognizer method processes available speech recognition services, it fails to properly validate or secure the default selection mechanism, allowing malicious applications to manipulate the recognizer chain. This insecure default value could be exploited through various attack vectors including direct manipulation of system services or through carefully crafted application interfaces that leverage the flawed method's logic. The vulnerability creates a path for local privilege escalation where an unprivileged application can effectively elevate its privileges by assuming control over speech recognition services that typically require elevated permissions. This type of flaw commonly maps to CWE-284 (Improper Access Control) and CWE-362 (Concurrent Execution using Shared Resource with Improper Synchronization) categories, reflecting both access control failures and potential race conditions in service initialization. The attack surface extends beyond simple privilege escalation to include potential data interception and unauthorized voice data processing capabilities that could compromise user privacy and system integrity.
The operational impact of CVE-2025-48629 extends beyond immediate privilege escalation to encompass broader security implications for Android device users and organizations relying on voice-enabled services. An attacker exploiting this vulnerability could gain persistent access to voice recognition services, potentially intercepting sensitive voice communications, accessing voice-activated device controls, and performing unauthorized actions through voice commands. The lack of user interaction requirements means that this vulnerability can be exploited silently in the background, making detection extremely difficult for end users and security monitoring systems. This flaw significantly weakens the Android security sandbox by allowing malicious applications to bypass the normal application permission model and gain access to system-level voice recognition services. Organizations deploying Android devices for enterprise use face particular risk as this vulnerability could enable unauthorized access to sensitive corporate voice communications and potentially provide attackers with persistent access to voice-activated security systems. The vulnerability's exploitation could also facilitate more complex attack chains including credential harvesting through voice-based authentication bypasses or as a stepping stone for additional privilege escalation attacks. From an ATT&CK framework perspective, this vulnerability aligns with techniques such as T1068 (Exploitation for Privilege Escalation) and T1547.001 (Registry Run Keys / Startup Folder) as it enables automatic privilege escalation without user interaction, potentially allowing attackers to maintain persistent access through manipulated system services.
Mitigation strategies for CVE-2025-48629 should focus on immediate system updates and enhanced monitoring of speech recognition service behaviors. Android device manufacturers and security administrators should prioritize applying the latest security patches and firmware updates that address the insecure default value in the findAvailRecognizer method. System administrators should implement monitoring solutions that track unusual speech recognition service activities and unauthorized changes to default recognizer assignments. Additional protective measures include enabling Android's built-in security features such as the secure voice recognition service restrictions, implementing application whitelisting for speech recognition services, and conducting regular security audits of voice-enabled applications. Organizations should also consider implementing network-level monitoring to detect potential unauthorized access to voice recognition services and establish incident response procedures specifically for voice-based security incidents. Device users should be advised to avoid installing untrusted applications that request excessive permissions and to regularly update their systems to prevent exploitation of this vulnerability. The vulnerability highlights the importance of proper input validation and secure default configuration in system services, emphasizing that even seemingly minor implementation flaws in core system components can create significant security risks. Security teams should also consider implementing behavioral analysis tools that can detect anomalous patterns in speech recognition service usage that might indicate exploitation attempts.