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    <link>https://vulnerability.circl.lu</link>
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    <lastBuildDate>Mon, 28 Sep 2026 17:18:54 +0000</lastBuildDate>
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      <title>CVE-2026-12570 — Denial of Service via HDF5 Shape Bomb in keras.models.load_model() in keras-team/keras</title>
      <link>https://vulnerability.circl.lu/vuln/cve-2026-12570</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; keras-team/keras&lt;/p&gt;
&lt;p&gt;A vulnerability in keras-team/keras versions &amp;lt;= 3.15.0 allows for a denial of service (DoS) attack when loading malicious .keras model files via the keras.models.load_model() function. The H5IOStore.__getitem__ method in keras/src/saving/saving_lib.py does not validate the shape or size of datasets, leading to unbounded memory allocation. A specially crafted .keras file can exploit this flaw to trigger an out-of-memory (OOM) condition, causing the process to be terminated (exit code 137). This issue bypasses the fix for CVE-2026-0897, which only addressed a similar vulnerability in KerasFileEditor. The attack vector includes poisoned models from public repositories or malicious model registries, posing a risk to machine learning pipelines that process untrusted models.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; keras-team/keras&lt;/p&gt;
&lt;p&gt;A vulnerability in keras-team/keras versions &amp;lt;= 3.15.0 allows for a denial of service (DoS) attack when loading malicious .keras model files via the keras.models.load_model() function. The H5IOStore.__getitem__ method in keras/src/saving/saving_lib.py does not validate the shape or size of datasets, leading to unbounded memory allocation. A specially crafted .keras file can exploit this flaw to trigger an out-of-memory (OOM) condition, causing the process to be terminated (exit code 137). This issue bypasses the fix for CVE-2026-0897, which only addressed a similar vulnerability in KerasFileEditor. The attack vector includes poisoned models from public repositories or malicious model registries, posing a risk to machine learning pipelines that process untrusted models.&lt;/p&gt;</content:encoded>
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      <title>GHSA-74m6-m3xx-3vmj — Keras model loading is vulnerable to denial of service through HDF5 shape bombs</title>
      <link>https://vulnerability.circl.lu/vuln/ghsa-74m6-m3xx-3vmj</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: keras&lt;/p&gt;
&lt;p&gt;A vulnerability in keras-team/keras versions &amp;lt; 3.15.0 allows for a denial of service (DoS) attack when loading malicious .keras model files via the keras.models.load_model() function. The H5IOStore.__getitem__ method in keras/src/saving/saving_lib.py does not validate the shape or size of datasets, leading to unbounded memory allocation. A specially crafted .keras file can exploit this flaw to trigger an out-of-memory (OOM) condition, causing the process to be terminated (exit code 137). This issue bypasses the fix for CVE-2026-0897, which only addressed a similar vulnerability in KerasFileEditor. The attack vector includes poisoned models from public repositories or malicious model registries, posing a risk to machine learning pipelines that process untrusted models.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: keras&lt;/p&gt;
&lt;p&gt;A vulnerability in keras-team/keras versions &amp;lt; 3.15.0 allows for a denial of service (DoS) attack when loading malicious .keras model files via the keras.models.load_model() function. The H5IOStore.__getitem__ method in keras/src/saving/saving_lib.py does not validate the shape or size of datasets, leading to unbounded memory allocation. A specially crafted .keras file can exploit this flaw to trigger an out-of-memory (OOM) condition, causing the process to be terminated (exit code 137). This issue bypasses the fix for CVE-2026-0897, which only addressed a similar vulnerability in KerasFileEditor. The attack vector includes poisoned models from public repositories or malicious model registries, posing a risk to machine learning pipelines that process untrusted models.&lt;/p&gt;</content:encoded>
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