CVE-2025-32434
PyTorch Remote Command Execution (RCE)
Description
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.
INFO
Published Date :
April 18, 2025, 4:15 p.m.
Last Modified :
May 28, 2025, 1:14 p.m.
Source :
[email protected]
Remotely Exploitable :
Yes !
Impact Score :
5.9
Exploitability Score :
3.9
Public PoC/Exploit Available at Github
CVE-2025-32434 has a 15 public PoC/Exploit available at Github.
Go to the Public Exploits tab to see the list.
References to Advisories, Solutions, and Tools
Here, you will find a curated list of external links that provide in-depth
information, practical solutions, and valuable tools related to
CVE-2025-32434.
| URL | Resource |
|---|---|
| https://github.com/pytorch/pytorch/security/advisories/GHSA-53q9-r3pm-6pq6 | Vendor Advisory |
We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).
None
Python Jupyter Notebook
AI-powered M&A target discovery platform using LangChain, Streamlit, and custom ML models
Python Shell
None
Python Jupyter Notebook Shell
None
Python
None
Python
Jobless AI — an AI with nothing but time to help you land a job in tech.
Python CSS JavaScript HTML Dockerfile Makefile
None
Jupyter Notebook Python Shell Dockerfile HTML CSS Jinja
None
Python
None
Python Shell
Core engine (SibyllAI) for music spotting and analysis
Python Shell
Blueprint for Ingesting massive volumes of live or archived videos and extract insights for summarization and interactive Q&A
Shell Python CSS HTML Jupyter Notebook Dockerfile Jinja
Blueprint for Ingesting massive volumes of live or archived videos and extract insights for summarization and interactive Q&A
Shell Python CSS HTML Jupyter Notebook Dockerfile Jinja
Blueprint for Ingesting massive volumes of live or archived videos and extract insights for summarization and interactive Q&A
Shell JavaScript Python CSS HTML Jupyter Notebook Dockerfile Jinja
None
Python
A comprehensive Python toolkit for local deployment of Microsoft's Florence-2 vision model. Process images with state-of-the-art computer vision capabilities including object detection, image captioning, and visual analysis.
Python Shell
Results are limited to the first 15 repositories due to potential performance issues.
The following list is the news that have been mention
CVE-2025-32434 vulnerability anywhere in the article.
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Kaspersky
Update PyTorch ASAP | Kaspersky official blog
vulnerability Researchers have found a way to exploit a security mechanism in a popular machine-learning framework. April 22, 2025 A researcher has discovered a vulnerability in PyTorch – an open-sour ... Read more
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The Cyber Express
Critical Security Vulnerability Found in WordPress Plugin InstaWP Connect
The Moroccan authorities have warned users of a critical vulnerability in the popular WordPress plugin, InstaWP Connect. The General Directorate of Information Systems Security (DGSSI), which operates ... Read more
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The Cyber Express
Senators Peters and Rounds Lead Bipartisan Push to Extend Critical Cybersecurity Information Sharing Protections
U.S. Senators Gary Peters (D-MI) and Mike Rounds (R-SD) have introduced a bipartisan bill to extend vital provisions from the Cybersecurity Information Sharing Act of 2015. The new legislation, titled ... Read more
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Daily CyberSecurity
Cellebrite Android Zero-Day Exploit PoC Released: CVE-2024-53104
A security researcher published a proof-of-concept exploit code for an Android zero-day exploit chain developed by Cellebrite to unlock the device of a student activist in the country and attempt to i ... Read more
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Daily CyberSecurity
Critical PyTorch Vulnerability CVE-2025-32434 Allows Remote Code Execution
A critical vulnerability has been unearthed in PyTorch, one of the most beloved deep learning frameworks out there. Security researcher Ji’an Zhou has identified a critical Remote Command Execution (R ... Read more
The following table lists the changes that have been made to the
CVE-2025-32434 vulnerability over time.
Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.
-
Initial Analysis by [email protected]
May. 28, 2025
Action Type Old Value New Value Added CVSS V3.1 AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H Added CPE Configuration OR *cpe:2.3:a:linuxfoundation:pytorch:*:*:*:*:*:python:*:* versions up to (excluding) 2.6.0 Added Reference Type GitHub, Inc.: https://github.com/pytorch/pytorch/security/advisories/GHSA-53q9-r3pm-6pq6 Types: Vendor Advisory -
New CVE Received by [email protected]
Apr. 18, 2025
Action Type Old Value New Value Added Description 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. Added CVSS V4.0 AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X Added CWE CWE-502 Added Reference https://github.com/pytorch/pytorch/security/advisories/GHSA-53q9-r3pm-6pq6
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2025-32434 is
associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification
(CAPEC)
stores attack patterns, which are descriptions of the common attributes and
approaches employed by adversaries to exploit the CVE-2025-32434
weaknesses.