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 tensorflow/tensorflow to version 2.2.1, 2.3.1 or higher.
Affected versions of this package are vulnerable to Unchecked Return Value. In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes an invalid argument to dlpack.to_dlpack the expected validations will cause variables to bind to nullptr while setting a status variable to the error condition. However, this status argument is not properly checked. Hence, code following these methods will bind references to null pointers. This is undefined behavior and reported as an error if compiling with -fsanitize=null. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.
Note: Refer to https://security.snyk.io/vuln/SNYK-PYTHON-TENSORFLOW-1013606