Google TensorFlow up to 2.7.1/2.8.0/2.9.0 QuantizedAdd min_input/max_input denial of service

Summaryinfo

A vulnerability categorized as problematic has been discovered in Google TensorFlow up to 2.7.1/2.8.0/2.9.0. This issue affects the function QuantizedAdd. Such manipulation of the argument min_input/max_input leads to denial of service. This vulnerability is documented as CVE-2022-35967. The attack can be executed remotely. There is not any exploit available. It is advisable to upgrade the affected component.

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 rated as problematic. Affected by this issue is the function QuantizedAdd. The manipulation of the argument min_input/max_input with an unknown input leads to a denial of service vulnerability. Using CWE to declare the problem leads to CWE-404. The product does not release or incorrectly releases a resource before it is made available for re-use. Impacted is availability. CVE summarizes:

TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. 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 released 09/17/2022 as GHSA-v6h3-348g-6h5x. The advisory is shared for download at github.com. This vulnerability is handled as CVE-2022-35967 since 07/15/2022. There are known technical details, but no exploit is available. The MITRE ATT&CK project declares the attack technique as T1499.

Upgrading to version 2.7.2, 2.8.1, 2.9.1 or 2.10.0 eliminates this vulnerability. Applying the patch 49b3824d83af706df0ad07e4e677d88659756d89 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.

Once again VulDB remains the best 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

Once again VulDB remains the best source for vulnerability data.

Discussion