Pytorch
CVE-2025-4287
MEDIUM
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A05:2021 - Security Misconfiguration
ASVS 5.0
V15 - Secure Coding and Architecture Resource release
|
| Impact | CVSS score of 4.8 (MEDIUM). Attack characteristics: local attack vector, low complexity, low privileges required, no user interaction not required. EPSS exploitation probability: 0.08%. |
| Exploit ScenarioDerived | Successful exploitation could compromise the medium-severity affected system. |
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Alert meAnalysisAIv1 – Mar 28, 2026
A vulnerability was found in PyTorch 2.6.0+cu124. Rated medium severity (CVSS 4.8), this vulnerability is low attack complexity. No vendor patch available.
RemediationAI
No vendor patch is available at time of analysis. Monitor vendor advisories for updates. Apply vendor patches when available. Implement network segmentation and monitoring as interim mitigations.
Affected ProductsAI
See vendor advisory for affected versions.
Affects your stack
Find out whether the stacks and servers you run are on an affected version.
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
This vulnerability is classified under CWE-404. A vulnerability was found in PyTorch 2.6.0+cu124. It has been rated as problematic. Affected by this issue is the function torch.cuda.nccl.reduce of the file torch/cuda/nccl.py. The manipulation leads to denial of service. It is possible to launch the attack on the local host. The exploit has been disclosed to the public and may be used. The patch is identified as 5827d2061dcb4acd05ac5f8e65d8693a481ba0f5. It is recommended to apply a patch to fix this issue.
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Severity by source
CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
Primary rating from NVD.
CVSS VectorNVD
DescriptionCVE.org
A vulnerability was found in PyTorch 2.6.0+cu124. It has been rated as problematic. Affected by this issue is the function torch.cuda.nccl.reduce of the file torch/cuda/nccl.py. The manipulation leads to denial of service. It is possible to launch the attack on the local host. The exploit has been disclosed to the public and may be used. The patch is identified as 5827d2061dcb4acd05ac5f8e65d8693a481ba0f5. It is recommended to apply a patch to fix this issue.
Executive ViewAI
Organizations using A vulnerability should be aware of moderate risk from CVE-2025-4287 rated CVSS 4.8. Exploitation could compromise the security of affected deployments. Organizations should apply vendor updates when available and monitor for exploitation.
Apply vendor patch. If patching is delayed: restrict network access and enable monitoring.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Denial of Service attacks render applications or systems unavailable by overwhelming resources or triggering failure conditions.
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In PyTorch <=2.4.1, the RemoteModule has Deserialization RCE. Rated critical severity (CVSS 9.8), this vulnerability is
PickleScan before 0.0.23 can be bypassed by flipping specific ZIP file header flag bits, allowing malicious pickle files
In PyTorch before trunk/89695, torch.jit.annotations.parse_type_line can cause arbitrary code execution because eval is
PyTorch is a Python package that provides tensor computation. [CVSS 8.8 HIGH]
A vulnerability in lightning-ai/pytorch-lightning version 2.3.2 allows an attacker to cause a denial of service by sendi
Out-of-bounds heap read in PyTorch torchvision's native GIF decoder (versions through 0.28.0) lets attackers who supply
picklescan before 0.0.23 is vulnerable to a ZIP archive manipulation attack that causes it to crash when attempting to e
TorchServe is a flexible and easy-to-use tool for serving and scaling PyTorch models in production. Rated critical sever
PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built
NVIDIA APEX for Linux contains a deserialization of untrusted data vulnerability that affects environments using PyTorch
A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124. Rated medium severity (CVSS
NVD
CVE.org
EPSS
GitHub
VulDB
Exploit-DB