Описание
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.
Ссылки
- PatchThird Party Advisory
- Third Party Advisory
- ExploitThird Party Advisory
- PatchThird Party Advisory
- Third Party Advisory
- ExploitThird Party Advisory
Уязвимые конфигурации
EPSS
6.3 Medium
CVSS3
3.5 Low
CVSS2
Дефекты
Связанные уязвимости
In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` impl ...
EPSS
6.3 Medium
CVSS3
3.5 Low
CVSS2