Google TensorFlow up to 2.8.4/2.9.3/2.10.1/2.11 Output Channels CONV_3D_TRANSPOSE buffer overflow

Summaryinfo

A vulnerability, which was classified as critical, has been found in Google TensorFlow up to 2.8.4/2.9.3/2.10.1/2.11. The impacted element is the function CONV_3D_TRANSPOSE of the component Output Channels Handler. The manipulation leads to buffer overflow. This vulnerability is referenced as CVE-2022-41894. Remote exploitation of the attack is possible. No exploit is available. It is advisable to upgrade the affected component.

Detailsinfo

A vulnerability was found in Google TensorFlow up to 2.8.4/2.9.3/2.10.1/2.11 (Artificial Intelligence Software) and classified as critical. This issue affects the function CONV_3D_TRANSPOSE of the component Output Channels Handler. The manipulation with an unknown input leads to a buffer overflow vulnerability. Using CWE to declare the problem leads to CWE-120. The product copies an input buffer to an output buffer without verifying that the size of the input buffer is less than the size of the output buffer, leading to a buffer overflow. Impacted is confidentiality, integrity, and availability. The summary by CVE is:

TensorFlow is an open source platform for machine learning. The reference kernel of the `CONV_3D_TRANSPOSE` TensorFlow Lite operator wrongly increments the data_ptr when adding the bias to the result. Instead of `data_ptr += num_channels;` it should be `data_ptr += output_num_channels;` as if the number of input channels is different than the number of output channels, the wrong result will be returned and a buffer overflow will occur if num_channels > output_num_channels. An attacker can craft a model with a specific number of input channels. It is then possible to write specific values through the bias of the layer outside the bounds of the buffer. This attack only works if the reference kernel resolver is used in the interpreter. We have patched the issue in GitHub commit 72c0bdcb25305b0b36842d746cc61d72658d2941. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

The weakness was published 11/19/2022 as GHSA-h6q3-vv32-2cq5. It is possible to read the advisory at github.com. The identification of this vulnerability is CVE-2022-41894 since 09/30/2022. It demands that the victim is doing some kind of user interaction. Technical details of the vulnerability are known, but there is no available exploit. The pricing for an exploit might be around USD $0-$5k at the moment (estimation calculated on 12/20/2022).

Upgrading eliminates this vulnerability. Applying the patch 72c0bdcb25305b0b36842d746cc61d72658d2941 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.

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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
• 2.8
• 2.8.0
• 2.8.1
• 2.8.2
• 2.8.3
• 2.8.4
• 2.9
• 2.9.0
• 2.9.1
• 2.9.2
• 2.9.3
• 2.10
• 2.10.0
• 2.10.1
• 2.11

License

• free

Website

• Vendor: https://www.google.com/

CPE 2.3info

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CPE 2.2info

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