PyTorch Tuple Handler is Vulnerable to Memory Corruption through Manipulation of None Argument

Exploitation

No confirmed exploitation recorded. Patch Next marks exploitation only from CISA KEV.

CVSS 4.0

2.3 · CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:P/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N · score source

EPSS

• CVE-2025-2148: 0.44% estimated exploitation activity in the next 30 days; percentile 38.02 (FIRST EPSS, 2026-11-03). This is a model estimate, not proof of exploitation or customer exposure.

As published by the source; long descriptions are shortened.

A vulnerability was found in PyTorch 2.6.0+cu124. It has been declared as critical. Affected by this vulnerability is the function torch.ops.profiler.callendcallbacksonjitfut of the component Tuple Handler. The manipulation of the argument None leads to memory corruption. The attack can be launched remotely. The complexity of an attack is rather high. The exploitation appears to be difficult.

Published by the source

10 Mar 2025, 12:30 UTC

Last modified by the source

9 Jun 2026, 21:26 UTC

Source last checked

26 Oct 2026, 13:45 UTC

1. Revision 3 · amended · 26 Oct 2026

   Amended from ghsa record GHSA-c678-jfcj-6jmf

2. Revision 2 · amended · 24 Oct 2026

   Reviewed OSV alias/range/CVSS4 correction; package source scopes and original publication preserved. No customer finding resolved.

3. Revision 1 · created · 24 Oct 2026

   Published from osv record GHSA-c678-jfcj-6jmf

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# Patch Next advisory brief: CVE-2025-2148

Advisory: PyTorch Tuple Handler is Vulnerable to Memory Corruption through Manipulation of None Argument
IDs: CVE-2025-2148, GHSA-c678-jfcj-6jmf
Record: https://patchnext.com/advisories/cve-2025-2148 (revision 3, source checked 26 Oct 2026, 13:45 UTC)
Inventory: none attached. This brief comes from a public page and does not say whether any deployment is affected.
Severity: Low (CVSS 2.3)
Exploitation: no confirmed exploitation recorded. Patch Next confirms exploitation only from CISA KEV.
Vendor response: Vendor response not established. A vendor fix does not mean a deployment is fixed.

## Affected components
- PyPI torch: affected <= 2.6.0

## Suggested inspection (read-only)
- `python -m pip show torch`: prints the installed version. Run with the environment that serves production active.

## Supported action
No complete vendor fix is recorded. Follow the primary source's mitigation guidance and check this record again before closing anything.

## Required regression checks
- Run the test suite and a production build.
- Exercise the features that depend on torch.
- Repeat the inspection and confirm that only fixed versions remain installed.

## Rollback considerations
- Keep the previous lockfile and deployment artifact. Rolling back reinstates the vulnerable version, so apply any documented mitigation while you fix forward.

## Unresolved questions
- Which deployments run an affected version?
- Exploitation status can change. Check again before lowering the priority.
- Mark the work resolved only after the fixed version is verified in production.

## Sources
- Verified: https://osv.dev/vulnerability/GHSA-c678-jfcj-6jmf (OSV record GHSA-c678-jfcj-6jmf lists affected ranges: PyPI torch >=0 <=2.6.0)
- Verified: https://github.com/advisories/GHSA-c678-jfcj-6jmf (GitHub-reviewed advisory GHSA-c678-jfcj-6jmf lists affected ranges: PyPI torch >=0 <=2.6.0)

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