What is the CVSS score of CVE-2025-46153?

CVE-2025-46153 has a CVSS 3.1 base score of 5.3 (Medium). CVSS vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N. EPSS exploitation probability: 0.1%.

Which versions of AI / ML are affected by CVE-2025-46153?

Organizations using PyTorch before 3.7.0 should be aware of moderate risk from CVE-2025-46153 rated CVSS 5.3. Exploitation could compromise the security of affected deployments.. A patch is available.

How to fix or mitigate CVE-2025-46153?

Within 30 days: Identify affected systems and apply vendor patches as part of regular patch cycle. Vendor patch is available.

AI / ML CVE-2025-46153

MEDIUM

Inefficient CPU Computation (CWE-1176)

2025-09-25 cve@mitre.org

Information Disclosure Red Hat AI / ML Pytorch Suse

5.3

CVSS 3.1

CVSS VectorNVD

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

Attack Vector

Network

Attack Complexity

Low

Privileges Required

None

User Interaction

None

Scope

Unchanged

Confidentiality

Low

Integrity

None

Availability

None

Lifecycle Timeline

Analysis Generated

Mar 28, 2026 - 19:14 vuln.today

Patch released

Mar 28, 2026 - 19:14 nvd

Patch available

CVE Published

Sep 25, 2025 - 15:16 nvd

MEDIUM 5.3

Blast Radius

ecosystem impact

† from your stack dependencies † transitive graph · vuln.today resolves 4-path depth

332 pypi packages depend on torch (293 direct, 41 indirect)

Ecosystem-wide dependent count for version 2.6.0.

DescriptionNVD

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.

AnalysisAI

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,. Rated medium severity (CVSS 5.3), this vulnerability is remotely exploitable, no authentication required, low attack complexity.

Technical ContextAI

This vulnerability is classified under CWE-1176. 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. Affected products include: Linuxfoundation Pytorch. Version information: before 3.7.0.

RemediationAI

A vendor patch is available. Apply the latest security update as soon as possible. Apply vendor patches when available. Implement network segmentation and monitoring as interim mitigations.