CVE-2026-1462
A vulnerability in the `TFSMLayer` class of the `keras` package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of `.keras` models, even when `safe_mode=True`. This bypasses the security guarantees of `safe_mode` and enables arbitrary attacker-controlled code execution during model inference under the victim's privileges. The issue arises due to the unconditional loading of external SavedModels, serialization of attacker-controlled file paths, and the lack of validation in the `from_config()` method.
Schwachstellenklasse
A vulnerability in the `TFSMLayer` class of the `keras` package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of `.keras` models, even when `safe_mode=True`. This bypasses the security guarantees of `safe_mode` and enables arbitrary attacker-controlled code execution during model inference under the victim's privileges. The issue arises due to the unconditional loading of external SavedModels, serialization of attacker-controlled file paths, and the lack of validation in the `from_config()` method.
Betroffene Produkte
- keras keras
- redhat openshift_ai
Quellen
- https://github.com/keras-team/keras/commit/b6773d3decaef1b05d8e794458e148cb362f163f
- https://huntr.com/bounties/7e78d6f1-6977-4300-b595-e81bdbda331c
- https://access.redhat.com/errata/RHSA-2026:24977
- https://access.redhat.com/errata/RHSA-2026:37275
- https://access.redhat.com/security/cve/CVE-2026-1462
- https://bugzilla.redhat.com/show_bug.cgi?id=2457856
Finden Sie die Schwachstelle, bevor es ein Angreifer tut.
Melden Sie sich mit GitHub an und starten Sie Ihr erstes Audit in weniger als einer Minute. Für den kostenlosen Plan ist keine Kreditkarte nötig.