CVE-2025-21479 is a high-severity vulnerability identified in multiple Qualcomm Snapdragon platforms and associated components, including various FastConnect modules, Snapdragon mobile platforms across generations, and wireless connectivity chips. The vulnerability is classified under CWE-863, indicating an incorrect authorization issue. Specifically, this flaw arises from memory corruption caused by unauthorized command execution within the GPU micronode when a specific sequence of commands is processed. The GPU micronode is a critical subcomponent responsible for handling graphics processing tasks at a low level. An attacker exploiting this vulnerability could execute unauthorized commands that corrupt memory, potentially leading to arbitrary code execution, privilege escalation, or denial of service. The CVSS v3.1 score of 8.6 reflects the high impact on confidentiality, integrity, and availability, with an attack vector requiring local access (AV:L), low attack complexity (AC:L), no privileges required (PR:N), but user interaction needed (UI:R), and scope change (S:C). This means an attacker must have local access and trick a user into interaction, but once exploited, the impact extends beyond the vulnerable component to affect the entire system. The affected product list is extensive, covering a wide range of Snapdragon SoCs and connectivity modules used in smartphones, tablets, IoT devices, and compute platforms. No public exploits are currently known, and no patches have been linked yet, indicating that mitigation may rely on vendor updates and cautious operational practices. Given the widespread deployment of Snapdragon platforms globally, this vulnerability represents a significant risk vector, especially in devices where GPU micronode commands can be influenced by untrusted applications or users.

For European organizations, the impact of CVE-2025-21479 can be substantial due to the widespread use of Qualcomm Snapdragon chipsets in mobile devices, embedded systems, and IoT devices prevalent in enterprise and consumer environments. Confidentiality could be compromised if attackers leverage this vulnerability to execute arbitrary code and access sensitive data stored or processed on affected devices. Integrity risks arise from potential unauthorized command execution leading to system manipulation or malware persistence. Availability could be disrupted through memory corruption causing device crashes or denial of service. Enterprises relying on mobile devices for secure communications, remote work, or operational technology could face increased risk of data breaches, espionage, or operational disruption. The requirement for local access and user interaction somewhat limits remote exploitation but does not eliminate risk, especially in scenarios involving social engineering or insider threats. Additionally, the scope change in the vulnerability means that exploitation could affect multiple system components, amplifying the potential damage. The lack of current public exploits provides a window for mitigation, but the absence of patches necessitates proactive risk management. Overall, European organizations with large mobile device fleets or IoT deployments using affected Snapdragon platforms must prioritize vulnerability assessment and mitigation to avoid compromise.

1. Monitor Qualcomm and device vendor advisories closely for official patches or firmware updates addressing CVE-2025-21479 and apply them promptly once available. 2. Implement strict application whitelisting and privilege controls on devices to limit the ability of untrusted or malicious applications to execute GPU micronode commands or interact with vulnerable components. 3. Educate users on the risks of social engineering attacks that could trigger user interaction required for exploitation, emphasizing caution with unsolicited prompts or applications. 4. Employ mobile device management (MDM) solutions to enforce security policies, restrict installation of unverified apps, and monitor device behavior for anomalies indicative of exploitation attempts. 5. For IoT and embedded devices using affected chipsets, isolate them on segmented networks to reduce the risk of local attacker access and lateral movement. 6. Conduct regular security assessments and penetration testing focusing on local privilege escalation and GPU-related attack vectors to identify potential exploitation paths. 7. Maintain up-to-date inventories of devices and chipsets in use to prioritize patching and risk mitigation efforts effectively. 8. Where possible, disable or restrict GPU micronode functionalities not required for device operation to reduce attack surface.