Pytorch
CVE-2025-32434
CRITICAL
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A08:2025 - Software or Data Integrity Failures
ASVS 5.0
V1 - Encoding and Sanitization Safe deserialization, type allowlists
MITRE ATT&CK
2 techniques across 2 tactics: Execution, Initial Access The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Impact | CVSS score of 9.3 (CRITICAL). Attack characteristics: network attack vector, low complexity, no privileges required, no user interaction not required. EPSS exploitation probability: 1.22%. |
| Exploit ScenarioDerived | A remote attacker could execute arbitrary code through malicious serialized objects by sending crafted requests to the affected application. No authentication is required to exploit this vulnerability. |
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Alert meAnalysisAIv1 – Mar 28, 2026
PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. Rated critical severity (CVSS 9.3), this vulnerability is remotely exploitable, no authentication required, low attack complexity. No vendor patch available.
RemediationAI
No vendor patch is available at time of analysis. Monitor vendor advisories for updates. Avoid deserializing untrusted data. Use safe serialization formats (JSON). Implement integrity checks and type allowlists.
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in pypi
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 as Deserialization of Untrusted Data (CWE-502), which allows attackers to execute arbitrary code through malicious serialized objects. PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0. Affected products include: Linuxfoundation Pytorch. Version information: version 2.5.1.
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- Exploit and PoC references, threat intelligence from 22 sources
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Severity by source
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
Primary rating from GitHub Advisory · only source for this CVE.
CVSS VectorGitHub Advisory
Lifecycle Timeline
2DescriptionGitHub Advisory
PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0.
Executive ViewAI
Organizations using PyTorch face critical risk from CVE-2025-32434, a insecure deserialization vulnerability rated CVSS 9.3. Insecure deserialization could allow attackers to execute arbitrary code by providing crafted serialized data. Organizations should apply vendor updates immediately when available and implement compensating controls in the interim.
Apply vendor patch. If immediate patching is not feasible: (1) Restrict deserialization endpoints; (2) Implement integrity checks on serialized data; (3) Use type-safe alternatives.
Threat Intelligence Overview
NVD
CVE.org
EPSS
GitHub
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
Insecure deserialization occurs when an application converts serialized data (a stream of bytes representing an object's state) back into a living object without proper validation.
Affected Products (CPE)GitHub Advisory
TorchServe is a tool for serving and scaling PyTorch models in production. Rated critical severity (CVSS 9.8), this vuln
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
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
A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0.cuda.memory.caching_allocator_dele
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