CVE-2025-59509 in Windows
Summary
by MITRE • 11/11/2025
Insertion of sensitive information into sent data in Windows Speech allows an authorized attacker to disclose information locally.
If you want to get best quality of vulnerability data, you may have to visit VulDB.
Analysis
by VulDB Data Team • 01/05/2026
This vulnerability resides in the Windows Speech recognition and text-to-speech functionality where sensitive information can be inadvertently included in data sent to external systems. The flaw represents a data exposure issue that occurs when the speech processing components fail to properly sanitize or filter user input before transmitting it to remote destinations. The vulnerability specifically affects the Windows Speech API and related text-to-speech services that handle user interactions and voice commands. Attackers with local access can exploit this weakness to capture and exfiltrate sensitive data that users might have spoken or typed while using speech-enabled applications. The vulnerability demonstrates a classic information disclosure pattern where system components unintentionally propagate confidential information through communication channels.
The technical implementation of this vulnerability stems from insufficient input validation and data sanitization within the Windows Speech subsystem. When users interact with speech-enabled applications or system features, the underlying speech processing engine may include contextual information, metadata, or even direct user input in transmitted data packets. This occurs because the system does not adequately distinguish between legitimate speech processing data and potentially sensitive information that should remain local. The flaw is particularly concerning as it operates at the system level where speech recognition and synthesis components interact with various applications and services. The vulnerability allows attackers to harvest information that might include personal data, passwords, or other confidential content that users have spoken or entered through voice commands.
The operational impact of this vulnerability extends beyond simple information disclosure as it creates persistent exposure risks for users of speech-enabled systems. Local attackers who have established presence on a compromised system can leverage this vulnerability to continuously monitor and extract sensitive information from speech processing activities. The attack vector is particularly dangerous because speech recognition is commonly used for authentication, personal assistant functions, and various productivity applications where users naturally provide sensitive information. This vulnerability affects the fundamental security posture of Windows systems by creating covert channels through which attackers can harvest data without explicit user awareness. The risk is amplified in enterprise environments where voice-enabled systems are prevalent for accessibility features, automated customer service, or hands-free computing scenarios.
Mitigation strategies should focus on implementing comprehensive data filtering and sanitization within the Windows Speech subsystem. System administrators should ensure that speech processing components are configured to exclude sensitive information from external communications and that proper access controls are enforced on speech-enabled applications. The recommended approach includes disabling unnecessary speech features in environments where data confidentiality is paramount, implementing network monitoring to detect anomalous data transmission patterns, and applying timely security updates from Microsoft. Organizations should also consider implementing application whitelisting policies that restrict which applications can access speech processing APIs and establish clear guidelines for handling sensitive data in voice-enabled environments. This vulnerability aligns with CWE-200 (Information Exposure) and represents a significant concern under ATT&CK technique T1531 (Account Access Removal) and T1074 (Data Staged) where attackers can harvest information through legitimate system functions. The security controls should address both the immediate vulnerability and broader information protection requirements for voice-enabled computing environments.