Advisories for Pypi/Pytorch-Lightning package

PyTorch-Lightning versions 2.6.0 and earlier contain an insecure deserialization vulnerability (CWE-502) in the checkpoint loading mechanism. The LightningModule.load_from_checkpoint() method, which is commonly used to load saved model states, internally calls torch.load() without setting the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the Pickle module. A remote attacker can exploit this by providing a maliciously crafted checkpoint file, leading to arbitrary code execution on …

Security Advisory: Compromise of PyTorch Lightning PyPI Package Versions Published: 2026-04-30 Last Updated: 2026-05-12 Github Advisory: CVE-2026-44484 We have identified a security incident affecting certain versions of one of our PyPI packages. What happened We have determined that one or more released versions of this package have been compromised and include malicious code. Our current investigation indicates that the affected versions have introduced functionality consistent with a credential harvesting mechanism. …

In lightning-ai/pytorch-lightning version 2.3.2, a vulnerability exists in the LightningApp when running on a Windows host. The vulnerability occurs at the /api/v1/upload_file/ endpoint, allowing an attacker to write or overwrite arbitrary files by providing a crafted filename. This can lead to potential remote code execution (RCE) by overwriting critical files or placing malicious files in sensitive locations.

A vulnerability in lightning-ai/pytorch-lightning version 2.3.2 allows an attacker to cause a denial of service by sending an unexpected POST request to the /api/v1/state endpoint of LightningApp. This issue occurs due to improper handling of unexpected state values, which results in the server shutting down.

PyTorch Lightning version 1.5.10 and prior is vulnerable to code injection. An attacker could execute commands on the target OS running the operating system by setting the PL_TRAINER_GPUS when using the Trainer module. A patch is included in the 1.6.0 release.

pytorch-lightning is vulnerable to Deserialization of Untrusted Data.