Bug 2398183 (CVE-2025-46153)

Summary: CVE-2025-46153 torch: PyTorch inconsistent results
Product: [Other] Security Response Reporter: OSIDB Bzimport <bzimport>
Component: vulnerabilityAssignee: Product Security <prodsec-ir-bot>
Status: NEW --- QA Contact:
Severity: medium Docs Contact:
Priority: medium    
Version: unspecifiedCC: alinfoot, anpicker, bbrownin, bparees, dtrifiro, haoli, hasun, hkataria, jajackso, jcammara, jfula, jkoehler, jmitchel, jneedle, jowilson, jwong, kegrant, koliveir, kshier, lphiri, mabashia, nyancey, ometelka, pbraun, ptisnovs, rbryant, shvarugh, simaishi, smcdonal, stcannon, syedriko, teagle, tfister, thavo, ttakamiy, weaton, xdharmai, yguenane
Target Milestone: ---Keywords: Security
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Hardware: All   
OS: Linux   
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A consistency flaw has been discovered in the PyTorch library. PyTorch 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.
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oVirt Team: --- RHEL 7.3 requirements from Atomic Host:
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Description OSIDB Bzimport 2025-09-25 15:02:45 UTC
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.