A vulnerability was found in PyTorch 2.6.0. It has been rated as critical. Affected by this issue is the function torch.nn.utils.rnn.unpack_sequence. The manipulation leads to memory corruption. Attacking locally is a requirement. The exploit has been disclosed to the public and may be used. A patch is available through commit [4945180](https://github.com/pytorch/pytorch/commit/494518046816d29099b7d056a74ffa5c244fdcdd).
Update torch to 2.9.1 if you use the affected versions. Test the change in a non-production environment first.
Local check
hol-guard supply-chain scanPyTorch is vulnerable to memory corruption through its unpack_sequence function affects torch (pip). Severity is medium. A vulnerability was found in PyTorch 2.6.0. It has been rated as critical. Affected by this issue is the function torch.nn.utils.rnn.unpack_sequence. The manipulation leads to memory corruption. Attacking locally is a requirement. The exploit has been disclosed to the public and may be used. A patch is available through commit [4945180](https://github.com/pytorch/pytorch/commit/494518046816d29099b7d056a74ffa5c244fdcdd).
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 | <2.9.1 | 2.9.1 |
Fixed versions are reported by the source feed; confirm compatibility before updating.
A vulnerability was found in PyTorch 2.6.0. It has been rated as critical. Affected by this issue is the function torch.nn.utils.rnn.unpack_sequence. The manipulation leads to memory corruption. Attacking locally is a requirement. The exploit has been disclosed to the public and may be used. A patch is available through commit [4945180](https://github.com/pytorch/pytorch/commit/494518046816d29099b7d056a74ffa5c244fdcdd).
Update torch to 2.9.1 if you use the affected versions. Test the change in a non-production environment first.
Local check
hol-guard supply-chain scanPyTorch is vulnerable to memory corruption through its unpack_sequence function affects torch (pip). Severity is medium. A vulnerability was found in PyTorch 2.6.0. It has been rated as critical. Affected by this issue is the function torch.nn.utils.rnn.unpack_sequence. The manipulation leads to memory corruption. Attacking locally is a requirement. The exploit has been disclosed to the public and may be used. A patch is available through commit [4945180](https://github.com/pytorch/pytorch/commit/494518046816d29099b7d056a74ffa5c244fdcdd).
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 | <2.9.1 | 2.9.1 |
Fixed versions are reported by the source feed; confirm compatibility before updating.
Reported by GitHub Security Advisories (ghsa).
HOL Guard can help your team review package activity against supported protection paths.
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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