Medium severity · published Sep 25, 2020
CVE-2020-15198
In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor
5.4
CVSS
0.5%
EPSS
No
On KEV
Description
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 the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
CVSS vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N
Attack vector
Network
Complexity
High
Privileges
None
User interaction
None
Confidentiality
Low
Integrity
Low
Availability
None
Scope
Changed
Exploitation
Is it being used?
Exploit prediction (EPSS)0.5% · higher than 45% of CVEs
Exploited in the wildNo evidence yet
CISA KEVNot listed
Ransomware campaign useNot known
Affected products
Which versions
TE
Tensorflow · Google
2.3.0 before 2.3.1 · source: NVD
Affected product
TE
Tensorflow
Google
More from Tensorflow
9.9
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
9.8
CVE-2023-25668
TensorFlow is an open source platform for machine learning
9.8
CVE-2023-25664
TensorFlow is an open source platform for machine learning
9.8
CVE-2022-41900
TensorFlow is an open source platform for machine learning
9.8
CVE-2022-35939
TensorFlow is an open source platform for machine learning