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 the victim's system when the file is loaded.
A remote code execution (RCE) vulnerability exists in the lightning-ai/pytorch-lightning library version 2.2.1 due to improper handling of deserialized user input and mismanagement of dunder attributes by the `deepdiff` library. The library uses `deepdiff.Delta` objects to modify application state based on frontend actions. However, it is possible to bypass the intended restrictions on modifying dunder attributes, allowing an attacker to construct a serialized delta that passes the deserializer whitelist and contains dunder attributes. When processed, this can be exploited to access other modules, classes, and instances, leading to arbitrary attribute write and total RCE on any self-hosted pytorch-lightning application in its default configuration, as the delta endpoint is enabled by default.