CVE-2023-5091 is a high-severity Use After Free (UAF) vulnerability identified in the Arm Ltd Valhall GPU Kernel Driver, specifically affecting versions from r37p0 through r40p0. The Valhall architecture is a GPU microarchitecture used in various Arm Mali GPUs, which are widely integrated into mobile devices, embedded systems, and some specialized computing platforms. The vulnerability arises when a local, non-privileged user performs improper GPU processing operations that lead to accessing memory regions that have already been freed. This type of vulnerability, classified under CWE-416, can result in undefined behavior including memory corruption, data leakage, privilege escalation, or system crashes. The CVSS v3.1 score of 7.0 reflects a high severity, with the vector indicating that exploitation requires local access (AV:L), high attack complexity (AC:H), low privileges (PR:L), no user interaction (UI:N), and impacts confidentiality, integrity, and availability (C:H/I:H/A:H). Although no known exploits are currently reported in the wild, the vulnerability's nature suggests that an attacker with local access could leverage it to escalate privileges or execute arbitrary code within the kernel context, potentially compromising the entire system. The lack of available patches at the time of publication increases the urgency for mitigation and monitoring. This vulnerability is particularly critical because GPU drivers operate at a privileged level within the operating system, and exploitation could bypass traditional security boundaries. Given the widespread use of Arm Mali GPUs in consumer electronics and embedded devices, this vulnerability could have broad implications if exploited.

For European organizations, the impact of CVE-2023-5091 could be significant, especially for sectors relying on devices with Arm Mali GPUs, such as telecommunications, automotive, industrial control systems, and mobile computing. The vulnerability allows a local attacker to potentially escalate privileges and execute arbitrary code in kernel space, which could lead to full system compromise. This is particularly concerning for organizations that deploy embedded systems or mobile devices in critical infrastructure or sensitive environments. Confidentiality breaches could expose sensitive data processed or stored on affected devices. Integrity and availability impacts could disrupt operations, cause system instability, or enable persistent footholds for attackers. Since the vulnerability requires local access, the threat is heightened in environments where multiple users share devices or where attackers can gain physical or remote local access through other means. The absence of known exploits currently provides a window for proactive defense, but the high severity score and potential for privilege escalation necessitate immediate attention. European organizations with supply chains or products incorporating affected GPUs must assess their exposure and prioritize mitigation to prevent exploitation that could lead to data breaches, operational disruption, or reputational damage.

1. Inventory and Identification: Conduct a thorough inventory of devices and systems using Arm Mali GPUs with Valhall architecture versions r37p0 through r40p0 to identify affected assets. 2. Access Control Hardening: Restrict local access to affected devices to trusted users only. Implement strict user account management and monitor for unauthorized local access attempts. 3. System Updates and Vendor Coordination: Engage with Arm Ltd and device manufacturers to obtain patches or firmware updates as soon as they become available. Apply updates promptly to remediate the vulnerability. 4. Kernel and Driver Hardening: Where possible, apply kernel-level mitigations such as enabling kernel address space layout randomization (KASLR), kernel page-table isolation (KPTI), and other memory protection features to reduce exploitation risk. 5. Monitoring and Detection: Deploy host-based intrusion detection systems (HIDS) and monitor logs for unusual GPU driver activity or local privilege escalation attempts. 6. Network Segmentation: Limit network exposure of devices with affected GPUs to reduce the risk of attackers gaining local access via network vectors. 7. Incident Response Preparedness: Develop and test incident response plans specific to local privilege escalation and kernel-level compromises to ensure rapid containment if exploitation occurs. 8. User Education: Train users on the risks of local access vulnerabilities and the importance of device security, especially in shared or public environments. These measures, combined with timely patching, will significantly reduce the risk posed by this vulnerability.