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    <link>https://cve.radiocsirt.org</link>
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      <title>certfr-2026-avi-0873 — De multiples vulnérabilités ont été découvertes dans Microsoft Azure Linux. Elles permettent à un attaquant de provoque…</title>
      <link>https://cve.radiocsirt.org/vuln/certfr-2026-avi-0873</link>
      <description>certfr-2026-avi-0873</description>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/certfr-2026-avi-0873</guid>
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    <item>
      <title>EUVD-2026-331942</title>
      <link>https://cve.radiocsirt.org/vuln/euvd-2026-331942</link>
      <description>EUVD-2026-331942</description>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/euvd-2026-331942</guid>
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      <title>fkie_cve-2026-12480</title>
      <link>https://cve.radiocsirt.org/vuln/fkie_cve-2026-12480</link>
      <description>&lt;p&gt;Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim&amp;#39;s filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.2 and 3.14.1.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim&amp;#39;s filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.2 and 3.14.1.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/fkie_cve-2026-12480</guid>
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    <item>
      <title>GHSA-26c4-7vv6-867j — Keras: HDF5 virtual datasets can disclose local files</title>
      <link>https://cve.radiocsirt.org/vuln/ghsa-26c4-7vv6-867j</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: keras&lt;/p&gt;
&lt;p&gt;Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim&amp;#39;s filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.3 and 3.15.0.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: keras&lt;/p&gt;
&lt;p&gt;Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim&amp;#39;s filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.3 and 3.15.0.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/ghsa-26c4-7vv6-867j</guid>
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    <item>
      <title>msrc_CVE-2026-12480 — Arbitrary HDF5 File Read via Virtual Dataset Bypass in keras-team/keras</title>
      <link>https://cve.radiocsirt.org/vuln/msrc_cve-2026-12480</link>
      <description>msrc_CVE-2026-12480</description>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/msrc_cve-2026-12480</guid>
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    <item>
      <title>PYSEC-2026-3629 — Keras: HDF5 virtual datasets can disclose local files</title>
      <link>https://cve.radiocsirt.org/vuln/pysec-2026-3629</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: keras&lt;/p&gt;
&lt;p&gt;Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim&amp;#39;s filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.3 and 3.15.0.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: keras&lt;/p&gt;
&lt;p&gt;Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim&amp;#39;s filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.3 and 3.15.0.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/pysec-2026-3629</guid>
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    <item>
      <title>UBUNTU-CVE-2026-12480</title>
      <link>https://cve.radiocsirt.org/vuln/ubuntu-cve-2026-12480</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; Ubuntu:18.04:LTS: keras, Ubuntu:20.04:LTS: keras&lt;/p&gt;
&lt;p&gt;Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim&amp;#39;s filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.2 and 3.14.1.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; Ubuntu:18.04:LTS: keras, Ubuntu:20.04:LTS: keras&lt;/p&gt;
&lt;p&gt;Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim&amp;#39;s filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.2 and 3.14.1.&lt;/p&gt;</content:encoded>
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