3.5
CVSSv2

CVE-2020-15197

Published: 25/09/2020 Updated: 17/08/2021
CVSS v2 Base Score: 3.5 | Impact Score: 2.9 | Exploitability Score: 6.8
CVSS v3 Base Score: 6.3 | Impact Score: 4 | Exploitability Score: 1.8
VMScore: 312
Vector: AV:N/AC:M/Au:S/C:N/I:N/A:P

Vulnerability Summary

In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

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google tensorflow 2.3.0