The probability is the direct output of the EPSS model, and conveys an overall sense of the threat of exploitation in the wild. The percentile measures the EPSS probability relative to all known EPSS scores. Note: This data is updated daily, relying on the latest available EPSS model version. Check out the EPSS documentation for more details.
In a few clicks we can analyze your entire application and see what components are vulnerable in your application, and suggest you quick fixes.
Test your applicationsUpgrade Chainguard
tensorflow-gpu-jupyter
to version 2.20.0-r1 or higher.
Note: Versions mentioned in the description apply only to the upstream tensorflow-gpu-jupyter
package and not the tensorflow-gpu-jupyter
package as distributed by Chainguard
.
See How to fix?
for Chainguard
relevant fixed versions and status.
The Keras Model.load_model method can be exploited to achieve arbitrary code execution, even with safe_mode=True.
One can create a specially crafted .h5/.hdf5 model archive that, when loaded via Model.load_model, will trigger arbitrary code to be executed.
This is achieved by crafting a special .h5 archive file that uses the Lambda layer feature of keras which allows arbitrary Python code in the form of pickled code. The vulnerability comes from the fact that the safe_mode=True option is not honored when reading .h5 archives.
Note that the .h5/.hdf5 format is a legacy format supported by Keras 3 for backwards compatibility.