GHSA-9m3x-qqw2-h32h: picklescan: Deserialization enables RCE

### Summary An unsafe deserialization vulnerability allows any unauthenticated user to execute arbitrary code on the host loading a pickle payload from an untrusted source. ### Details It's possible to hide the `eval` call nested under another callable via `getattr`. ### PoC ```python import builtins class EvilClass: @staticmethod def _obfuscated_eval(payload): getattr(builtins, "eval")(payload) def __reduce__(self): payload = "__import__('os').system('echo \"successful attack\"')" return self._obfuscated_eval, (payload,) ``` ### Impact Who is impacted? Any organization or individual relying on picklescan to detect malicious pickle files from untrusted sources. What is the impact? Attackers can embed malicious code in pickle file that remains undetected but executes when the pickle file is loaded. Supply Chain Attack: Attackers can distribute infected pickle files to system that load serialized ML models, APIs, or saved Python objects from untrusted sources.

An adversary targets an MLOps platform that automatically pulls and benchmarks community-submitted models. They craft a malicious pickle file embedding a reverse shell via getattr obfuscation — the file passes picklescan inspection cleanly on pre-patch versions. The file is published to a public model hub or submitted as a model artifact via a pull request. When the automated evaluation pipeline loads the model for scoring, the payload executes with the privileges of the inference worker. The adversary gains shell access to the training infrastructure, from which they can exfiltrate training data, poison the model registry, harvest cloud credentials from environment variables, or persist access. No human interaction is required after initial artifact submission.