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VulnerabilityPublished Updated

CVE-2026-24747: PyTorch Vulnerable to Remote Code Execution via Untrusted Checkpoint Files

Affects pytorchSource GCVE Database

0

Not known to be exploited : upgrade to 2.10.0 soon.

Data as of 26 Oct 2026, 10:12 UTC

Severity
High

Rated by Threat Radar · No CVSS score from NVD or the CNA

EPSS
0.7% chance of exploitation in 30 days – higher than 56% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 2.10.0

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 29 Jan 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.

What to do

Upgrade pytorch to 2.10.0.

Affected software

ProductAffectedFixed in
Bitnamipytorchpkg:bitnami/pytorchOther threatsAffected
  • <2.10.0
Fixed in
  • 2.10.0

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

Upgrade PyTorch to version 2.10.0 or later, where this vulnerability is fixed. Avoid loading checkpoint files from untrusted sources using torch.load with weights_only=True. No other mitigations are indicated by the vendor advisory.

Description

A vulnerability in PyTorch prior to version 2.10.0 allows remote attackers to execute arbitrary code by crafting malicious checkpoint files (.pth) that exploit the weights_only unpickler. This flaw leads to memory corruption when loading such files with torch.load(..., weights_only=True). The issue is fixed in PyTorch 2.10.0.

References

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