Bug 2496097 (CVE-2026-12480)

Summary: CVE-2026-12480 keras: Keras: Information disclosure via malicious model archive with Virtual Dataset
Product: [Other] Security Response Reporter: OSIDB Bzimport <bzimport>
Component: vulnerabilityAssignee: Product Security DevOps Team <prodsec-dev>
Status: NEW --- QA Contact:
Severity: medium Docs Contact:
Priority: medium    
Version: unspecifiedCC: jkoehler, lphiri
Target Milestone: ---Keywords: Security
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Hardware: All   
OS: Linux   
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A flaw was found in Keras. An attacker can craft a malicious model archive or weights file containing a Virtual Dataset (VDS) that references external files on a victim's system. When a user loads this malicious model, the external file is transparently read. This vulnerability leads to information disclosure, allowing an attacker to access sensitive data from the victim's filesystem.
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Description OSIDB Bzimport 2026-07-01 18:02:19 UTC 
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'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.