CVE-2025-47398 in Snapdragon Auto
Summary
by MITRE • 02/02/2026
Memory Corruption while deallocating graphics processing unit memory buffers due to improper handling of memory pointers.
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Analysis
by VulDB Data Team • 03/09/2026
This vulnerability represents a critical memory corruption issue affecting gpu memory buffer deallocation processes within graphics processing unit systems. The flaw manifests when the system improperly handles memory pointers during the cleanup phase of gpu memory operations, creating potential pathways for arbitrary code execution or system instability. The root cause stems from inadequate validation and management of memory pointer references during deallocation routines, which can lead to heap corruption or null pointer dereferences. This type of vulnerability falls under the broader category of memory safety issues that are commonly classified as cwe-415 double free errors or cwe-476 null pointer dereference patterns, depending on the specific implementation details. The vulnerability affects systems where gpu memory management is handled through direct memory pointer manipulation rather than through safe memory allocation libraries. Attackers can potentially exploit this weakness by crafting malicious gpu memory operations that trigger the faulty pointer handling during deallocation, leading to memory corruption that may be leveraged for privilege escalation or denial of service conditions.
The operational impact of this vulnerability extends beyond simple memory corruption to encompass potential system compromise and stability degradation. When gpu memory buffers are deallocated with improper pointer handling, the system may experience crashes, application failures, or in more severe cases, allow attackers to execute arbitrary code within the gpu memory context. This is particularly concerning in environments where gpu acceleration is heavily utilized for graphics rendering, machine learning computations, or parallel processing tasks. The vulnerability can be exploited through various attack vectors including malicious graphics applications, compromised gpu drivers, or through indirect exploitation via gpu memory management interfaces. The memory corruption can manifest as heap overflows, use-after-free conditions, or other memory safety violations that may not be immediately apparent but can lead to persistent system instability. System administrators and security teams must consider this vulnerability as a potential entry point for advanced persistent threats that target gpu memory management subsystems.
Mitigation strategies for this vulnerability should focus on implementing robust memory pointer validation and introducing additional safety checks during gpu memory deallocation processes. Organizations should prioritize updating gpu drivers and system firmware to versions that address the memory pointer handling issues through proper null checks and memory validation routines. The implementation of address sanitizer tools and memory debugging utilities can help identify and prevent improper pointer operations during gpu memory management. Security measures should include monitoring for unusual gpu memory deallocation patterns and implementing runtime protections that detect and prevent memory corruption attempts. System hardening practices should incorporate memory safety libraries and safe memory allocation functions that prevent the types of pointer handling errors that lead to this vulnerability. Additionally, network segmentation and privilege separation can limit the potential impact of exploitation attempts, while regular security assessments should include gpu memory management validation to ensure proper pointer handling during deallocation operations. The vulnerability aligns with attack techniques documented in the attack pattern taxonomy under memory corruption exploitation methods and should be treated as a high-priority remediation item in cybersecurity risk management frameworks.