The snorkel library through version 0.10.0 contains an insecure deserialization vulnerability (CWE-502) in the MultitaskClassifier.load() method. This method loads model weight files using torch.load() without the weights_only=True parameter, which restricts deserialization to tensor objects. The default behavior permits deserialization of arbitrary Python objects via Pickle, which can be exploited by an attacker providing a crafted model file to achieve arbitrary code execution on the victim system when the file is loaded.

An attacker who can supply a maliciously crafted model file to the vulnerable load() method can achieve arbitrary code execution on the victim's system. This could lead to full system compromise depending on the privileges of the process running the vulnerable code. There are no known exploits in the wild at this time.

Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Until a fix is available, avoid loading untrusted or unauthenticated model files with the vulnerable MultitaskClassifier.load() method. Consider manually modifying the code to use torch.load() with weights_only=True if feasible and tested.