# CVE-2025-2953: PyTorch denial of service in torch.mkldnn_max_pool2d

Source: https://junglewise.ai/threats/cve-2025-2953-pytorch-denial-of-service-in-torch-mkldnn-max-pool2d  
Publisher: Junglewise Threat Intelligence, https://junglewise.ai/threats  
Published: 2025-03-30. Updated: 2026-06-08  
License: CC BY 4.0 with a link back

CVE-2025-2953 · Severity: low · CVSS 3.3 · Published 2025-03-30

PyTorch, a popular machine learning framework, is vulnerable to a local denial-of-service attack. An attacker with local access to a system running PyTorch can trigger a crash by providing specific parameters to a pooling function. This could lead to the interruption of machine learning workloads or service outages on affected systems.

Technologies: [torch (PyPI)](https://junglewise.ai/threats/technologies/torch), [PyTorch](https://junglewise.ai/threats/technologies/pytorch). Vendors: [PyPI](https://junglewise.ai/threats/vendors/pypi), [PyTorch](https://junglewise.ai/threats/vendors/pytorch).

## Quick answers

**Is CVE-2025-2953 exploited in the wild?** No. Junglewise Threat Intelligence has no report of CVE-2025-2953 being exploited in the wild.

**How severe is CVE-2025-2953?** Low severity, with a CVSS score of 3.3, published 30 March 2025.

**Which products and versions are affected?** torch (PyPI) < 2.7.1-rc1, ECOSYSTEM:introduced=0,fixed=2.7.1-rc1, ECOSYSTEM:introduced=0,last_affected=2.6.0+cu124; PyTorch < 2.7.1-rc1.

**Is there a fix for CVE-2025-2953?** Yes. torch (PyPI): upgrade to 2.7.1-rc1 or later. Junglewise finds every place you run it, drafts the upgrade and applies it once you approve.

**How is CVE-2025-2953 attacked?** It is attacked with local access, in a software library.

**Am I affected by CVE-2025-2953?** Check whether you run torch (PyPI) or PyTorch at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

## How to fix

- torch (PyPI): upgrade to 2.7.1-rc1 or later

  ```sh
  pip install "torch>=2.7.1-rc1"
  ```


## Technical details

A vulnerability in PyTorch versions prior to 2.7.1-rc1 allows a local attacker to cause a denial of service (DoS) via a floating point exception. The issue resides in the 'torch.mkldnn_max_pool2d' function, specifically when handling certain input parameters such as a 'stride' value of zero. This lack of proper error checking in the MKLDNN (oneDNN) integration leads to a process crash. Exploitation requires the ability to execute local Python code using the affected library. A fix is available in version 2.7.1-rc1.

## Affected products

- PyTorch PyTorch < 2.7.1-rc1

## Identifiers

- CVE-2025-2953
- GHSA-3749-ghw9-m3mg
- PYSEC-2025-191

## Timeline

- 2025-03-16: disclosed: Issue reported on GitHub
- 2025-03-30: advisory: GitHub and VulDB advisories published

## References

- [https://github.com/pytorch/pytorch/issues/149274](https://github.com/pytorch/pytorch/issues/149274)
- [https://github.com/pytorch/pytorch/issues/149274](https://github.com/pytorch/pytorch/issues/149274)
- [https://vuldb.com/?ctiid.302006](https://vuldb.com/?ctiid.302006)
- [https://vuldb.com/?id.302006](https://vuldb.com/?id.302006)
- [https://vuldb.com/?submit.521279](https://vuldb.com/?submit.521279)

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