Keras vulnerabilities
We track 5 vulnerabilities in Keras products. 5 are rated high or critical, and none are known to be exploited. The most recent was published on July 3, 2026.
Latest Keras vulnerabilities
- 9.8 Critical severity
keras-team/keras: Deserialization of Untrusted Data
A vulnerability in keras-team/keras version 3.14.0 allows for arbitrary code execution due to improper handling of deserialization in the `Lambda` layer. Specifically, the `_raise_for_lambda_deserialization()` function fails to enforce the safe-mode guard when
- 8.1 High severity
keras-team/keras: Improper Limitation of a Pathname to a Restricted Directory
Keras versions prior to 3.14.0 are vulnerable to a path traversal issue in the archive extraction utilities located in `keras/src/utils/file_utils.py`. The functions `filter_safe_tarinfos()` and `filter_safe_zipinfos()` validate archive member paths against th
- 7.8 High severity
keras-team/keras: Deserialization of Untrusted Data
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 `saf
- 8.9 High severity
Keras: Improper Limitation of a Pathname to a Restricted Directory
The keras.utils.get_file API in Keras, when used with the extract=True option for tar archives, is vulnerable to a path traversal attack. The utility uses Python's tarfile.extractall function without the filter="data" feature. A remote attacker can craft a mal
- 9.8 Critical severity
Keras: Deserialization of Untrusted Data
Deserialization of untrusted data can occur in versions of the Keras framework running versions 3.11.0 up to but not including 3.11.3, enabling a maliciously uploaded Keras file containing a TorchModuleWrapper class to run arbitrary code on an end user’s syste