pytorch-lightning vulnerabilities

PyTorch Lightning Arbitrary Code Execution via _instantiator Hyperparameter

PyTorch Lightning through 2.6.5, fixed in commit d710d68, contains a remote code execution vulnerability in the _load_state function that imports and executes attacker-controlled module names from checkpoint _instantiator hyperparameters. Attackers can craft malicious checkpoint files that bypass weights_only=True protections to execute arbitrary code when LightningModule.load_from_checkpoint is called.

• Update to 2.6.6

Compromise of PyTorch Lightning PyPi Package Versions

PyTorch Lightning is a deep learning framework to pretrain and finetune AI models. Versions 2.6.2 and 2.6.2 have introduced functionality consistent with a credential harvesting mechanism.

• Update to 2.6.4

CVE-2026-31221

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.

Denial of Service in lightning-ai/pytorch-lightning

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.

Arbitrary File Write/Overwrite in lightning-ai/pytorch-lightning

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.

• Update to 2.4.0

Arbitrary File Write via /v1/runs API endpoint in lightning-ai/pytorch-lightning

A vulnerability in the /v1/runs API endpoint of lightning-ai/pytorch-lightning v2.2.4 allows attackers to exploit path traversal when extracting tar.gz files. When the LightningApp is running with the plugin_server, attackers can deploy malicious tar.gz plugins that embed arbitrary files with path traversal vulnerabilities. This can result in arbitrary files being written to any directory in the victim's local file system, potentially leading to remote code execution.

• Update to 2.3.3

RCE via Property/Class Pollution in lightning-ai/pytorch-lightning

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

• Update to 2.3.3

Code Injection in pytorchlightning/pytorch-lightning

Code Injection in GitHub repository pytorchlightning/pytorch-lightning prior to 1.6.0.

• Update to 1.6.0

Deserialization of Untrusted Data in pytorchlightning/pytorch-lightning

pytorch-lightning is vulnerable to Deserialization of Untrusted Data

• Update to 1.6.0