https://cve.radiocsirt.org Contains only the most 10 recent entries. http://www.rssboard.org/rss-specification python-feedgen en Fri, 02 Oct 2026 23:29:03 +0000 https://cve.radiocsirt.org/vuln/cve-2026-1462 <p><strong>Affected:</strong> keras-team/keras, Red Hat OpenShift AI 2.25, Red Hat OpenShift AI 3.3, Red Hat OpenShift AI (RHOAI)</p> <p>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&#39;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.</p> <p><strong>Affected:</strong> keras-team/keras, Red Hat OpenShift AI 2.25, Red Hat OpenShift AI 3.3, Red Hat OpenShift AI (RHOAI)</p> <p>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&#39;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.</p> https://cve.radiocsirt.org/vuln/cve-2026-1462 https://cve.radiocsirt.org/vuln/ghsa-4f3f-g24h-fr8m <p><strong>Affected:</strong> PyPI: keras</p> <p>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&#39;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.</p> <p><strong>Affected:</strong> PyPI: keras</p> <p>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&#39;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.</p> https://cve.radiocsirt.org/vuln/ghsa-4f3f-g24h-fr8m