Is CVE-2025-63396 exploited in the wild?

No. Junglewise Threat Intelligence has no report of CVE-2025-63396 being exploited in the wild.

How severe is CVE-2025-63396?

Low severity, with a CVSS score of 3.3, published 12 November 2025.

Which products and versions are affected?

torch (PyPI) ECOSYSTEM:introduced=0,last_affected=2.5.0-NA,last_affected=2.7.1-NA.

Is there a fix for CVE-2025-63396?

No fixed version is recorded yet. Check the vendor's advisory in the references below. If you run it, Junglewise drafts a mitigation that fits your setup and applies it once you approve, with senior security engineers behind it.

How is CVE-2025-63396 attacked?

It is attacked with local access, in a software library.

Am I affected by CVE-2025-63396?

Check whether you run torch (PyPI) 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.

CVE-2025-63396: PyTorch denial of service in torch.profiler.profile

CVE-2025-63396 · Severity: low · CVSS 3.3 · Published 2025-11-12

A vulnerability in the PyTorch machine learning library can cause applications to crash or stop responding. This occurs when the performance profiling tool is used but not properly shut down, leading to a denial-of-service condition. This could disrupt AI model training or inference tasks, potentially impacting operational uptime for developers and researchers.

Technologies: torch (PyPI). Vendors: PyPI.

Quick answers

Is CVE-2025-63396 exploited in the wild?: No. Junglewise Threat Intelligence has no report of CVE-2025-63396 being exploited in the wild.
How severe is CVE-2025-63396?: Low severity, with a CVSS score of 3.3, published 12 November 2025.
Which products and versions are affected?: torch (PyPI) ECOSYSTEM:introduced=0,last_affected=2.5.0-NA,last_affected=2.7.1-NA.
Is there a fix for CVE-2025-63396?: No fixed version is recorded yet. Check the vendor's advisory in the references below. If you run it, Junglewise drafts a mitigation that fits your setup and applies it once you approve, with senior security engineers behind it.
How is CVE-2025-63396 attacked?: It is attacked with local access, in a software library.
Am I affected by CVE-2025-63396?: Check whether you run torch (PyPI) 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.

Technical details

A vulnerability classified as Improper Locking (CWE-667) exists in PyTorch v2.5 and v2.7.1 within the torch.profiler.profile (PythonTracer) component. The root cause is the omission of the profiler.stop() call, which can cause the application to crash (segmentation fault) or hang during the finalization process. An attacker with local access and the ability to execute code using the affected library can trigger this condition to cause a Denial of Service (DoS). The issue is documented in PyTorch GitHub issue #156563.

Affected products

Linux Foundation PyTorch 2.5, 2.7.1

Identifiers

CVE-2025-63396
PYSEC-2025-210

Timeline

2025-11-12: disclosed
2025-11-12: advisory

References

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