Google TensorFlow up to 2.7.1/2.8.0/2.9.0 list_kernels.cc TensorListReserve num_elements assertion

Summaryinfo

A vulnerability was found in Google TensorFlow up to 2.7.1/2.8.0/2.9.0. It has been rated as problematic. This affects the function TensorListReserve of the file core/kernels/list_kernels.cc. Performing a manipulation of the argument num_elements results in assertion. This vulnerability is reported as CVE-2022-35960. The attack is possible to be carried out remotely. No exploit exists. Upgrading the affected component is advised.

Detailsinfo

A vulnerability was found in Google TensorFlow up to 2.7.1/2.8.0/2.9.0 (Artificial Intelligence Software). It has been classified as problematic. This affects the function TensorListReserve of the file core/kernels/list_kernels.cc. The manipulation of the argument num_elements with an unknown input leads to a assertion vulnerability. CWE is classifying the issue as CWE-617. The product contains an assert() or similar statement that can be triggered by an attacker, which leads to an application exit or other behavior that is more severe than necessary. This is going to have an impact on availability. The summary by CVE is:

TensorFlow is an open source platform for machine learning. In `core/kernels/list_kernels.cc's TensorListReserve`, `num_elements` is assumed to be a tensor of size 1. When a `num_elements` of more than 1 element is provided, then `tf.raw_ops.TensorListReserve` fails the `CHECK_EQ` in `CheckIsAlignedAndSingleElement`. We have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

The weakness was disclosed 09/17/2022 as GHSA-v5xg-3q2c-c2r4. It is possible to read the advisory at github.com. This vulnerability is uniquely identified as CVE-2022-35960 since 07/15/2022. Technical details of the vulnerability are known, but there is no available exploit.

Upgrading to version 2.7.2, 2.8.1, 2.9.1 or 2.10.0 eliminates this vulnerability. Applying the patch b5f6fbfba76576202b72119897561e3bd4f179c7 is able to eliminate this problem. The bugfix is ready for download at github.com. The best possible mitigation is suggested to be upgrading to the latest version.

Be aware that VulDB is the high quality source for vulnerability data.

Productinfo

Type

• Artificial Intelligence Software

Vendor

• Google

Name

• TensorFlow

Version

• 2.0
• 2.1
• 2.2
• 2.3
• 2.4
• 2.5
• 2.6
• 2.7
• 2.7.0
• 2.7.1
• 2.8
• 2.8.0
• 2.9.0

License

• free

Website

• Vendor: https://www.google.com/

CPE 2.3info

• 🔍
• 🔍
• 🔍

CPE 2.2info

• 🔍
• 🔍
• 🔍

CVSSv4info

CVSSv3info

CVSSv2info

Exploitinginfo

Threat Intelligenceinfo

Countermeasuresinfo

Timelineinfo

Sourcesinfo

Entryinfo

Be aware that VulDB is the high quality source for vulnerability data.

Discussion