Vulnerabilities

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.

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.

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.

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 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.

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.

Lightning Network Daemon (lnd) is an implementation of a lightning bitcoin overlay network node. All lnd nodes before version `v0.15.4` are vulnerable to a block parsing bug that can cause a node to enter a degraded state once encountered. In this degraded state, nodes can continue to make payments and forward HTLCs, and close out channels. Opening channels is prohibited, and also on chain transaction events will be undetected. This can cause loss of funds if a CSV expiry is researched during a breach attempt or a CLTV delta expires forgetting the funds in the HTLC. A patch is available in `lnd` version 0.15.4. Users are advised to upgrade. Users unable to upgrade may use the `lncli updatechanpolicy` RPC call to increase their CLTV value to a very high amount or increase their fee policies. This will prevent nodes from routing through your node, meaning that no pending HTLCs can be present.

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

pytorch-lightning is vulnerable to Deserialization of Untrusted Data

Lightning Labs lnd before 0.13.3-beta allows loss of funds because of dust HTLC exposure.

Prior to 0.11.0-beta, LND (Lightning Network Daemon) had a vulnerability in its invoice database. While claiming on-chain a received HTLC output, it didn't verify that the corresponding outgoing off-chain HTLC was already settled before releasing the preimage. In the case of a hash-and-amount collision with an invoice, the preimage for an expected payment was instead released. A malicious peer could have deliberately intercepted an HTLC intended for the victim node, probed the preimage through a colluding relayed HTLC, and stolen the intercepted HTLC. The impact is a loss of funds in certain situations, and a weakening of the victim's receiver privacy.

This affects all versions of package lightning-server. It is possible to inject malicious JavaScript code as part of a session controller.

Lightning Network Daemon (lnd) before 0.7 allows attackers to trigger loss of funds because of Incorrect Access Control.