The Ludwig framework versions through 0.10.4 are vulnerable to insecure deserialization (CWE-502) due to the use of torch.load() without the weights_only=True parameter in the model serving component. This default behavior permits deserialization of arbitrary Python objects via pickle, enabling remote attackers to execute arbitrary code by supplying a maliciously crafted PyTorch model file to the ludwig serve command. The vulnerability has a CVSS 3.1 base score of 9.8, indicating critical severity with network attack vector, no required privileges or user interaction, and impacts confidentiality, integrity, and availability.

Successful exploitation allows an attacker to execute arbitrary code on the system hosting the Ludwig model server, potentially leading to full system compromise. The vulnerability affects confidentiality, integrity, and availability of the affected system. There are no known exploits in the wild at this time.

Patch status is not yet confirmed — no official fix or remediation guidance is currently available from the vendor. Users should monitor the vendor advisory for updates. Until a fix is released, avoid loading untrusted PyTorch model files with the ludwig serve command or consider manual mitigation by modifying the code to use torch.load() with weights_only=True if feasible.