PyTorch torch.jit.jit_module_from_flatbuffer memory corruption

published 2025-04-02 last yr. modified 2026-09-08 2mo ago also BIT-pytorch-2025-3121 , EUVD-2025-15087 , PYSEC-2025-196

cvss: 3.3; version 3.1, CNA
cisa kev: Not listed; not in CISA's catalog
epss: 0.3%; EPSS 0.3% chance of exploitation in 30 days, percentile 20%
public exploits: 0; none known

A vulnerability classified as problematic has been found in PyTorch 2.6.0. Affected is the function torch.jit.jit_module_from_flatbuffer. The manipulation leads to memory corruption. Local access is required to approach this attack. The exploit has been disclosed to the public and may be used.

Patch / fix

fixed in 1

bitnami pytorch 2.7.0

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Vendor advisories

What the vendors themselves say about their products: affected, fixed or not affected, and what to do.

red hat product security vex CVE-2025-3121 updated 2026-06-28 cvss 3.3

PyTorch: PyTorch torch.jit.jit_module_from_flatbuffer memory corruption

Red Hat All currently supported Red Hat products
not affected: vulnerable code not present

Red Hat CSAF VEX © Red Hat, Inc., from https://security.access.redhat.com/data/csaf/v2/vex/; changed: reduced to product statuses and remediations. CC BY 4.0 · csaf

CISA SSVC

Exploitation: Proof of concept is public
Automatable: no
Technical impact: partial
Assessed: last yr. (2025-04-03)

Exploit prediction

0.28% chance of exploitation in the next 30 days, higher than 20% of all scored CVEs (FIRST EPSS, 2026-11-09).

Exploits and checks

github.com https://github.com/pytorch/pytorch/issues/149800#issue-2940240700 referenced PoC, tagged "exploit" by a source, unverified
vuldb.com https://vuldb.com/?submit.525049 referenced PoC, tagged "exploit" by a source, unverified

CVSS scores

assigned by	version	score	vector
CNA	4.0	4.8	CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
CNA	3.1	3.3	CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
CNA	3.0	3.3	CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
CNA	2.0	1.7	AV:L/AC:L/Au:S/C:N/I:N/A:P
CNA	4.0	4.8	CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
NVD	3.1	5.5	CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
OSV	3.1	5.5	CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Affected packages

ecosystem	package	affected	fixed in
bitnami	pytorch	>=2.6.0, <2.7.0	2.7.0
pypi	torch	<=2.6.0-NA	no fix listed

Affected products

n/a PyTorch

Classification

Weakness

CWE-119 Improper Restriction of Operations within the Bounds of a Memory Buffer

References

github.com /pytorch/pytorch/issues/149800#issue-2940240700
exploit, issue-tracking, vendor-advisory, advisory, report
vuldb.com /?submit.525049
third-party-advisory, exploit, vdb-entry, advisory, evidence
github.com /pytorch/pytorch/issues/149800
issue-tracking, vendor-advisory, advisory, report
vuldb.com /?id.303012
vdb-entry, technical-description, third-party-advisory, advisory
vuldb.com /?ctiid.303012
signature, permissions-required, vdb-entry, report
nvd.nist.gov /vuln/detail/CVE-2025-3121
web

Sources

Fencer Intel keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.