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The _load_model() function in the neural_magic_training.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f (2024-07-21) allows arbitrary code execution. When a user supplies a directory path via the --model command-line argument, the function reads a module.py file from that directory and executes its contents directly using Python's exec() function. This design does not validate or sanitize the file's content, allowing an attacker who controls the input directory to execute arbitrary Python code in the context of the process running the script.
nebuly
The torch-checkpoint-shrink.py script in the ml-engineering project in commit 0099885db36a8f06556efe1faf552518852cb1e0 (2025-20-27) contains an insecure deserialization vulnerability (CWE-502). The script uses torch.load() to process PyTorch checkpoint files (.pt) without enabling the security-restrictive weights_only=True parameter. This oversight 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 in the context of the user running the script.
Microdot is a minimalistic Python web framework. Prior to 2.6.1, the Response.set_cookie() method does not sanitize its string arguments, and in particular will not detect the presence of the \r\n sequence in them. This can be a potential source of header injection attacks. For a header injection attack through this issue to be possible, an attacker must first infiltrate the client (for example through an independent XSS attack), so that it can send malicious information that is destined to be stored in a cookie by the server on behalf of the victim. An attacker that infiltrates one client can only orchestrate a header injection attack for that client, all other clients that were not infiltrated are safe. This vulnerability is fixed in 2.6.1.
