A vulnerability was found in PyTorch 2.6.0. It has been declared as critical. Affected by this vulnerability is the function torch.nn.utils.rnn.pad_packed_sequence. 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.
Monitor this advisory for an available fix and review any installs of the affected package.
Local check
hol-guard supply-chain scanPyTorch is Vulnerable to Memory Consumption through pad_packed_sequence Function affects torch (pip). Severity is medium. A vulnerability was found in PyTorch 2.6.0. It has been declared as critical. Affected by this vulnerability is the function torch.nn.utils.rnn.pad_packed_sequence. 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.
AI coding agents often install or upgrade packages automatically in pip. A medium vulnerability in a dependency can be pulled into a project through a normal install or update without a human reviewing the change, expanding the blast radius from a single package to every agent workspace that depends on it.
| Package | Affected range | Fixed version |
|---|---|---|
| torchpip | <=2.6.0 | Not reported |
A vulnerability was found in PyTorch 2.6.0. It has been declared as critical. Affected by this vulnerability is the function torch.nn.utils.rnn.pad_packed_sequence. 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.
Monitor this advisory for an available fix and review any installs of the affected package.
Local check
hol-guard supply-chain scanPyTorch is Vulnerable to Memory Consumption through pad_packed_sequence Function affects torch (pip). Severity is medium. A vulnerability was found in PyTorch 2.6.0. It has been declared as critical. Affected by this vulnerability is the function torch.nn.utils.rnn.pad_packed_sequence. 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.
AI coding agents often install or upgrade packages automatically in pip. A medium vulnerability in a dependency can be pulled into a project through a normal install or update without a human reviewing the change, expanding the blast radius from a single package to every agent workspace that depends on it.
| Package | Affected range | Fixed version |
|---|---|---|
| torchpip | <=2.6.0 | Not reported |
Reported by GitHub Security Advisories (ghsa).
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Explore HOL GuardReported by GitHub Security Advisories (ghsa).
HOL Guard can help your team review package activity against supported protection paths.
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