EUVD-2025-208972Severity by source
AV:A/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H
Primary rating from NVD · only source for this CVE.
CVSS VectorNVD
CVSS:3.1/AV:A/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H
Lifecycle Timeline
3DescriptionCVE.org
NVIDIA APEX for Linux contains a vulnerability where an unauthorized attacker could cause a deserialization of untrusted data. This vulnerability affects environments that use PyTorch versions earlier than 2.6. A successful exploit of this vulnerability might lead to code execution, denial of service, escalation of privileges, data tampering, and information disclosure.
AnalysisAI
NVIDIA APEX for Linux contains a deserialization of untrusted data vulnerability that affects environments using PyTorch versions earlier than 2.6. An attacker with low privileges on an adjacent network can exploit this flaw to achieve code execution, denial of service, privilege escalation, data tampering, and information disclosure with scope change (CVSS 9.0 Critical). No KEV listing or public POC availability has been reported at this time.
Technical ContextAI
NVIDIA APEX (A PyTorch Extension) is a tool for mixed precision and distributed training in PyTorch environments, commonly used to accelerate deep learning workloads. The vulnerability stems from CWE-502 (Deserialization of Untrusted Data), where the application fails to properly validate serialized data before processing it. This affects the cpe:2.3:a:nvidia:apex product across all versions when used with PyTorch versions prior to 2.6. Deserialization vulnerabilities occur when applications deserialize objects from untrusted sources without sufficient validation, allowing attackers to inject malicious serialized objects that execute arbitrary code during the deserialization process.
RemediationAI
The primary remediation is to upgrade PyTorch to version 2.6 or later, which mitigates the deserialization vulnerability in NVIDIA APEX environments, as detailed in the NVIDIA security advisory at https://nvidia.custhelp.com/app/answers/detail/a_id/5782. Organizations unable to immediately upgrade should implement network segmentation to restrict adjacent network access to APEX deployments, enforce strict authentication and authorization controls to limit low-privilege account access, and monitor for suspicious deserialization activities or unexpected process execution from APEX components. Consider implementing application-level input validation and restricting the sources from which serialized data is accepted until the PyTorch upgrade can be completed.
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External POC / Exploit Code
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