CVE-2026-47620 in Dynamo
Summary
by MITRE • 08/04/2026
NVIDIA Dynamo for Linux contains a vulnerability where an attacker could cause a race condition in the LoRA manager singleton initialization. A successful exploit of this vulnerability might lead to data tampering and denial of service.
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Analysis
by VulDB Data Team • 08/04/2026
The vulnerability in NVIDIA Dynamo for Linux represents a critical race condition flaw within the LoRA manager singleton initialization process that exposes the system to potential exploitation. This type of vulnerability falls under the CWE-362 category known as "Concurrent Execution using Shared Resource with Improper Synchronization" and aligns with ATT&CK technique T1499.004 for network denial of service attacks. The race condition occurs when multiple threads or processes attempt to access and initialize the same singleton resource simultaneously without proper locking mechanisms, creating a window where the system state can become inconsistent.
The technical implementation of this vulnerability stems from improper synchronization mechanisms during the singleton pattern execution within the LoRA manager component. When the initialization process begins, concurrent access attempts from different execution contexts can result in unpredictable behavior where multiple instances may be created or existing instances may be corrupted. This flaw specifically manifests in the dynamic loading and configuration of LoRA (Low-Rank Adaptation) models used for machine learning workflows, which are critical components in modern AI inference pipelines. The singleton pattern failure means that the manager responsible for coordinating these resources cannot guarantee consistent state management across concurrent operations.
The operational impact of this vulnerability extends beyond simple denial of service to include potential data tampering scenarios that could compromise the integrity of machine learning workloads. An attacker exploiting this race condition could manipulate the LoRA model configurations, potentially leading to incorrect inference results or unauthorized access to training data. The denial of service aspect occurs when concurrent initialization attempts cause the system to crash or become unresponsive, effectively preventing legitimate users from accessing the NVIDIA Dynamo services. This creates a significant risk for production environments where continuous availability and accurate processing are essential for maintaining business operations and AI model performance.
Mitigation strategies should focus on implementing proper synchronization mechanisms such as mutex locks, semaphores, or atomic operations during the singleton initialization process to prevent concurrent access conflicts. The implementation of double-checked locking patterns or other thread-safe initialization techniques would address the core issue by ensuring that only one initialization process can proceed at a time. Organizations should also consider implementing monitoring and alerting systems to detect anomalous behavior patterns that might indicate exploitation attempts. Additionally, regular updates and patches from NVIDIA should be applied promptly to address known vulnerabilities in the software stack, as this type of race condition is typically resolved through proper code review and concurrency control implementation. The fix would align with security best practices outlined in NIST SP 800-53 and ISO/IEC 27001 standards for managing concurrent access controls and system integrity protection measures.