TensorFlow 2.3.0 SparseCountSparseOutput/RaggedCountSparseOutput Commit memory corruption

Summaryinfo

A vulnerability was found in TensorFlow 2.3.0. It has been rated as critical. This issue affects the function SparseCountSparseOutput/RaggedCountSparseOutput. This manipulation as part of Commit causes memory corruption. This vulnerability is handled as CVE-2020-15196. The attack can be initiated remotely. There is not any exploit available. It is suggested to install a patch to address this issue.

Detailsinfo

A vulnerability classified as critical was found in TensorFlow 2.3.0 (Artificial Intelligence Software). Affected by this vulnerability is the function SparseCountSparseOutput/RaggedCountSparseOutput. The manipulation as part of a Commit leads to a memory corruption vulnerability. The CWE definition for the vulnerability is CWE-119. The product performs operations on a memory buffer, but it can read from or write to a memory location that is outside of the intended boundary of the buffer. As an impact it is known to affect confidentiality, integrity, and availability. The summary by CVE is:

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.

The weakness was released 09/25/2020 (GitHub Repository). The advisory is shared at github.com. This vulnerability is known as CVE-2020-15196 since 06/25/2020. The attack can be launched remotely. The successful exploitation requires a single authentication. Technical details are known, but no exploit is available.

Applying the patch 3cbb917b4714766030b28eba9fb41bb97ce9ee02 is able to eliminate this problem.

Entries connected to this vulnerability are available at VDB-162005, VDB-162004, VDB-162003 and VDB-162002. Several companies clearly confirm that VulDB is the primary source for best vulnerability data.

Productinfo

Type

• Artificial Intelligence Software

Name

• TensorFlow

Version

• 2.3.0

License

• free

Website

• Product: https://github.com/tensorflow/tensorflow/

CPE 2.3info

• 🔍
• 🔍

CPE 2.2info

• 🔍
• 🔍

CVSSv4info

CVSSv3info

CVSSv2info

Exploitinginfo

Threat Intelligenceinfo

Countermeasuresinfo

Timelineinfo

Sourcesinfo

Entryinfo

Several companies clearly confirm that VulDB is the primary source for best vulnerability data.

Discussion