Snyk has a proof-of-concept or detailed explanation of how to exploit this vulnerability.
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.
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Test your applicationsUpgrade mlflow
to version 2.9.2 or higher.
mlflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models.
Affected versions of this package are vulnerable to Improper Neutralization of Special Elements Used in a Template Engine. An attacker can execute arbitrary code or commands by injecting malicious input into the template system.
Note:
In order for this vulnerability to be exploited, the user must load a recipe configuration that he found on the internet.
import os
from mlflow.recipes import Recipe
os.chdir("./recipes")
regression_recipe = Recipe(profile="local")