CVE-2026-57554 in Snapdragon Auto
Summary
by MITRE • 10/06/2026
Memory Corruption when asynchronous threads access shared performance counter data simultaneously during FastRPC invocations.
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Analysis
by VulDB Data Team • 10/06/2026
The vulnerability described involves a critical memory corruption issue arising from race conditions within the FastRPC framework, specifically affecting the handling of shared performance counter data accessed by asynchronous threads. In complex software architectures that rely on remote procedure calls for inter-process communication or distributed computing tasks, maintaining thread safety is paramount when multiple execution contexts interact with shared resources. The specific flaw occurs during concurrent invocations where different asynchronous threads attempt to read from or write to a common memory region designated for performance metrics without adequate synchronization mechanisms such as mutexes, semaphores, or atomic operations. This lack of proper locking allows one thread to modify the data structure while another is in the middle of reading it, leading to inconsistent states within the application's internal logic and potentially corrupting adjacent memory regions due to buffer overflows or invalid pointer dereferences resulting from corrupted metadata.
From a technical perspective, this vulnerability aligns with CWE-362, which classifies concurrent execution using shared resources with improper synchronization as a race condition. The core issue lies in the failure of the FastRPC implementation to enforce mutual exclusion when accessing non-thread-safe data structures during high-concurrency scenarios. When asynchronous threads are spawned to handle multiple RPC requests simultaneously, they may all attempt to update performance counters that track metrics such as latency, throughput, or error rates. If these updates involve compound operations like read-modify-write sequences without atomicity guarantees, the final state of the counter becomes unpredictable and often incorrect. More severely, if the data structure includes pointers or length fields that are updated concurrently with their usage, an attacker who can trigger this race condition might manipulate memory layout in a way that facilitates arbitrary code execution or causes a denial of service through segmentation faults.
The operational impact of such a vulnerability is significant for systems relying on FastRPC for critical performance monitoring and control functions. In production environments, particularly those involving real-time processing or high-frequency trading applications where precise timing and data integrity are crucial, this flaw can lead to inaccurate telemetry data, making it difficult for administrators to diagnose issues based on faulty metrics. Beyond the immediate loss of accurate performance data, the memory corruption aspect poses a severe security risk. An attacker who understands the internal structure of the shared counter object could potentially craft malicious RPC payloads designed to exploit the race window, leading to heap overflow or stack-based buffer overflows depending on how the counters are implemented in memory. This can result in complete system compromise, allowing for privilege escalation, data exfiltration, or persistent backdoor installation if the affected service runs with elevated privileges.
Mitigation strategies must focus on enforcing strict thread safety within the FastRPC implementation and its associated performance monitoring subsystems. Developers should implement fine-grained locking mechanisms around all accesses to shared performance counter variables, ensuring that read and write operations are atomic relative to each other. Alternatively, using lock-free data structures with atomic instructions provided by modern processors can offer better performance while maintaining correctness in high-concurrency environments. Code reviews must specifically target asynchronous callback handlers and thread pools for proper synchronization patterns. Additionally, employing static analysis tools capable of detecting race conditions during the development phase is essential. For deployed systems, runtime protection mechanisms such as Address Sanitizers or hardware-enforced memory isolation can help detect these vulnerabilities earlier in the testing lifecycle before they reach production. Regular security audits focusing on concurrent access patterns to shared state are also recommended to ensure long-term resilience against this class of defects.