Kedro Org vulnerabilities

8 vulnerabilities

Known vulnerabilities in Kedro Org products, newest first, with CVSS severity, EPSS, KEV listings and ransomware use, across 4 products.

Products

4
7.1CVE-2026-111170kedro-orgkedro-datasets+1
EPSS score
0.39%
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.9.8CVE-2024-9701kedro-orgkedro-org/kedro+1
EPSS score
1.14%
A Remote Code Execution (RCE) vulnerability has been identified in the Kedro ShelveStore class (version 0.19.8). This vulnerability allows an attacker to execute arbitrary Python code via deserialization of malicious payloads, potentially leading to a full system compromise. The ShelveStore class uses Python's shelve module to manage session data, which relies on pickle for serialization. Crafting a malicious payload and storing it in the shelve file can lead to RCE when the payload is deserialized.8.8CVE-2024-12215kedro-orgkedro-org/kedro+1
EPSS score
1.08%
In kedro-org/kedro version 0.19.8, the `pull_package()` API function allows users to download and extract micro packages from the Internet. However, the function `project_wheel_metadata()` within the code path can execute the `setup.py` file inside the tar file, leading to remote code execution (RCE) by running arbitrary commands on the victim's machine.7.7CVE-2026-62997kedro-orgkedro-plugins
EPSS score
0.69%
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. The issue affects only the opt-in kedro_datasets_experimental component and does not affect users who load only trusted files. This issue is fixed in version 9.5.0.7.1CVE-2026-3840kedro-orgkedro-org/kedro+1
EPSS score
0.20%
A vulnerability in Kedro version 1.2.0 allows an attacker to exploit path traversal by providing a crafted version string. The `_get_versioned_path()` method in `kedro/io/core.py` directly interpolates user-supplied version strings into filesystem paths without sanitization. This enables an attacker to escape the intended versioned dataset directory and access files outside the expected path. The issue is also reachable through the CLI via the `--load-versions` parameter, as `_split_load_versions()` in `kedro/framework/cli/utils.py` does not validate the version string. This vulnerability can lead to unauthorized file reads, data poisoning, cross-project or cross-tenant data access, and broader downstream impacts in environments where Kedro is used with automation or orchestration layers.8.1CVE-2026-35167kedro-orgkedro+2
EPSS score
0.40%
Kedro is a toolbox for production-ready data science. Prior to 1.3.0, the _get_versioned_path() method in kedro/io/core.py constructs filesystem paths by directly interpolating user-supplied version strings without sanitization. Because version strings are used as path components, traversal sequences such as ../ are preserved and can escape the intended versioned dataset directory. This is reachable through multiple entry points: catalog.load(..., version=...), DataCatalog.from_config(..., load_versions=...), and the CLI via kedro run --load-versions=dataset:../../../secrets. An attacker who can influence the version string can force Kedro to load files from outside the intended version directory, enabling unauthorized file reads, data poisoning, or cross-tenant data access in shared environments. This vulnerability is fixed in 1.3.0.9.8CVE-2026-35171kedro-orgkedro+2
EPSS score
0.88%
Kedro is a toolbox for production-ready data science. Prior to 1.3.0, Kedro allows the logging configuration file path to be set via the KEDRO_LOGGING_CONFIG environment variable and loads it without validation. The logging configuration schema supports the special () key, which enables arbitrary callable instantiation. An attacker can exploit this to execute arbitrary system commands during application startup. This is a critical remote code execution (RCE) vulnerability caused by unsafe use of logging.config.dictConfig() with user-controlled input. This vulnerability is fixed in 1.3.0.6.5CVE-2026-35492kedro-orgkedro-plugins+1
EPSS score
0.45%
Kedro-Datasets is a Kendo plugin providing data connectors. Prior to 9.3.0, PartitionedDataset in kedro-datasets was vulnerable to path traversal. Partition IDs were concatenated directly with the dataset base path without validation. An attacker or malicious input containing .. components in a partition ID could cause files to be written outside the configured dataset directory, potentially overwriting arbitrary files on the filesystem. Users of PartitionedDataset with any storage backend (local filesystem, S3, GCS, etc.) are affected. This vulnerability is fixed in 9.3.0.