HIGH · 8.5

CVE-2020-15196

In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `...

Vulnerability Description

In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `DenseCountSparseOutput`, where both tensors are fully specified. In the sparse and ragged count weights are still accessed in parallel with the data. But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the heap buffer allocated for the weights. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

CVSS Score

8.5

HIGH

CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:H/I:H/A:H
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
LOW
User Interaction
NONE
Scope
CHANGED
Confidentiality
HIGH
Integrity
HIGH
Availability
HIGH

Affected Products

VendorProductVersions
GoogleTensorflow2.3.0

Related Weaknesses (CWE)

References

FAQ

What is CVE-2020-15196?

CVE-2020-15196 is a vulnerability with a CVSS score of 8.5 (HIGH). In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `...

How severe is CVE-2020-15196?

CVE-2020-15196 has been rated HIGH with a CVSS base score of 8.5/10. Review the CVSS metrics above for detailed severity breakdown.

Is there a patch for CVE-2020-15196?

Check the references section above for vendor advisories and patch information. Affected products include: Google Tensorflow.