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keras@2.13.1rc0 vulnerabilities

Multi-backend Keras

  • latest version

    3.12.0

  • latest non vulnerable version

    3.12.0

  • first published

    10 years ago

  • latest version published

    1 months ago

  • licenses detected

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    Direct Vulnerabilities

    Known vulnerabilities in the keras package. This does not include vulnerabilities belonging to this package’s dependencies.

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    VulnerabilityVulnerable Version
    • H
    Directory Traversal

    keras is a Keras is a high-level neural networks API for Python..

    Affected versions of this package are vulnerable to Directory Traversal via the keras.utils.get_file API when the extract=True option is used for tar archives. An attacker can write arbitrary files to any location on the filesystem outside of the intended destination folder by supplying a crafted tar archive containing special symlinks.

    Note:

    This vulnerability is linked to the underlying Python tarfile weakness, identified as CVE-2025-4517. Note that upgrading Python to one of the versions that fix CVE-2025-4517 (e.g. Python 3.13.4) is not enough. One additionally needs to upgrade Keras to a version with the fix (Keras 3.12.0).

    How to fix Directory Traversal?

    Upgrade keras to version 3.12.0 or higher.

    [,3.12.0)
    • M
    Deserialization of Untrusted Data

    keras is a Keras is a high-level neural networks API for Python..

    Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the .keras archives when they are initialized with a path to a vocabulary file. The model deserialization process when loading the archives abuses the StringLookup layer's vocabulary argument. An attacker can access arbitrary local files or trigger server-side requests to arbitrary network endpoints by supplying malicious file paths or URLs in the model configuration. This is possible even when safe_mode is set to True.

    How to fix Deserialization of Untrusted Data?

    Upgrade keras to version 3.12.0 or higher.

    [,3.12.0)
    • H
    Improper Control of Dynamically-Managed Code Resources

    keras is a Keras is a high-level neural networks API for Python..

    Affected versions of this package are vulnerable to Improper Control of Dynamically-Managed Code Resources via the Model.load_model method. An attacker can execute arbitrary code by providing a specially crafted .h5 or .hdf5 model archive that leverages the Lambda layer feature to include pickled Python code, which is executed when the archive is loaded, even if safe_mode=True is set.

    How to fix Improper Control of Dynamically-Managed Code Resources?

    Upgrade keras to version 3.11.3 or higher.

    [,3.11.3)
    • H
    Deserialization of Untrusted Data

    keras is a Keras is a high-level neural networks API for Python..

    Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the Model.load_model method. An attacker can execute arbitrary code by providing a specially crafted .keras model archive containing a config.json file that invokes keras.config.enable_unsafe_deserialization() to disable safe mode, followed by a Lambda layer with malicious pickled code.

    How to fix Deserialization of Untrusted Data?

    Upgrade keras to version 3.11.0 or higher.

    [,3.11.0)
    • H
    Deserialization of Untrusted Data

    keras is a Keras is a high-level neural networks API for Python..

    Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the function saving_lib.load_model, which identifies the model source (file, directory, or Hugging Face repository) and then calls the corresponding loader. An attacker can execute arbitrary code by convincing a user to load a specially crafted .keras model archive.

    How to fix Deserialization of Untrusted Data?

    Upgrade keras to version 3.11.0 or higher.

    [,3.11.0)
    • H
    Deserialization of Untrusted Data

    keras is a Keras is a high-level neural networks API for Python..

    Affected versions of this package are vulnerable to Deserialization of Untrusted Data in the load_model() function, which uses pickle for serialization. An attacker can execute code even if safe_mode is set to True, by supplying a malicious .keras file. The included config.json can be manipulated to point to and load npz model files containing executable code.

    How to fix Deserialization of Untrusted Data?

    Upgrade keras to version 3.9.0 or higher.

    [,3.9.0)
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