Kedro-Datasets vulnerabilities

kedro-datasets from 9.3.0 through 9.6.0 contains a path traversal vulnerability in MatplotlibDataset.save() that allows attackers to write files outside the dataset directory by supplying absolute plot names. Because validate_sub_path() strips leading slashes while pathlib's join discards the base path, attackers can create or overwrite files anywhere the process can write.

Kedro-Datasets provides data connectors for Kedro. From version 5.0.0 until 9.5.0, kedro_datasets_experimental.pytorch.PyTorchDataset in kedro-datasets loads .pt model files with torch.load without enforcing weights_only=True, and user-supplied load_args are silently dropped. On PyTorch versions earlier than 2.6, a malicious pickle-backed model from an attacker-influenced shared registry, downloaded checkpoint, or partitioned external source can execute arbitrary code when a Kedro pipeline loads it.

In Kedro-Datasets prior to 9.3.0, PartitionedDataset is vulnerable to path traversal because partition IDs are concatenated directly with the base path without validation. A malicious partition ID containing .. components can cause files to be written outside the configured directory, potentially overwriting arbitrary files.