Google TensorFlow up to 2.9.2/2.10.0 tf.keras.losses.poisson y_pred/y_true buffer size

Summaryinfo

A vulnerability, which was classified as problematic, was found in Google TensorFlow up to 2.9.2/2.10.0. Affected by this vulnerability is the function tf.keras.losses.poisson. Such manipulation of the argument y_pred/y_true leads to buffer size. This vulnerability is referenced as CVE-2022-41887. It is possible to launch the attack remotely. No exploit is available. You should upgrade the affected component.

Detailsinfo

A vulnerability, which was classified as problematic, has been found in Google TensorFlow up to 2.9.2/2.10.0 (Artificial Intelligence Software). Affected by this issue is the function tf.keras.losses.poisson. The manipulation of the argument y_pred/y_true with an unknown input leads to a buffer size vulnerability. Using CWE to declare the problem leads to CWE-131. The product does not correctly calculate the size to be used when allocating a buffer, which could lead to a buffer overflow. Impacted is availability. CVE summarizes:

TensorFlow is an open source platform for machine learning. `tf.keras.losses.poisson` receives a `y_pred` and `y_true` that are passed through `functor::mul` in `BinaryOp`. If the resulting dimensions overflow an `int32`, TensorFlow will crash due to a size mismatch during broadcast assignment. We have patched the issue in GitHub commit c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 and 2.9.3, as these are also affected and still in supported range. However, we will not cherrypick this commit into TensorFlow 2.8.x, as it depends on Eigen behavior that changed between 2.8 and 2.9.

The weakness was published 11/19/2022 as GHSA-8fvv-46hw-vpg3. The advisory is available at github.com. This vulnerability is handled as CVE-2022-41887 since 09/30/2022. Successful exploitation requires user interaction by the victim. Technical details are known, but there is no available exploit.

Upgrading eliminates this vulnerability. Applying the patch c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c 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
• 2.9
• 2.9.0
• 2.9.1
• 2.9.2
• 2.10.0

License

• free

Website

• Vendor: https://www.google.com/

CPE 2.3info

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CPE 2.2info

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