CVE-2025-46153

MEDIUMCVSS 5.3/10EPSS 0.39%

Last modified

CVE-2025-46153 is a medium-severity vulnerability rated 5.3/10 on the CVSS scale. PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True.. EPSS estimates a 0.39% chance of exploitation in the next 30 days.

Description

PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True.

Metrics

CVSS 3.1
5.3/10

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N

EPSS Probability
0.39%

30.9th percentile

Probability of exploitation in the next 30 days. Learn more

Weakness Enumeration

Affected Software

VendorProductVersions
LinuxfoundationPytorch>= 2.6.0, < 2.7.0

References

Timeline

Published
Last Modified
Status
Analyzed

Frequently Asked Questions

What is CVE-2025-46153?
PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True.
How severe is CVE-2025-46153?
CVE-2025-46153 has a CVSS score of 5.3/10 (MEDIUM severity). The EPSS model estimates a 0.39% probability of exploitation in the next 30 days.
How do I fix CVE-2025-46153?
Check the vendor references and advisories linked above for patched versions and mitigation guidance. You can also run a Strix scan to test if your systems are affected.

Are you affected by CVE-2025-46153?

Run a free Strix scan to check your systems for this vulnerability.

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Source: NVD / NIST