CVE-2020-15197
However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash.
Does this matter?
Lower severity and a low EPSS score (0.73%). Track it; it rarely justifies an emergency change on its own.
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 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.
- CVSS 3.1
- 6.3 MEDIUMCVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:N/I:N/A:H
- EPSS
- 0.73% probability · 52th percentile
- CISA KEV
- Not listed
- Weakness
- CWE-20, CWE-617
- Affected
- google/tensorflow
- Source
- security-advisories@github.com
References
- https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02Patch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1Third Party Advisory
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qc53-44cj-vfvxExploit, Third Party Advisory
- https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02Patch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1Third Party Advisory
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qc53-44cj-vfvxExploit, Third Party Advisory
Source: NVD record, EPSS from FIRST.org, KEV from CISA. Refreshed daily.