Google TensorFlow up to 2.7.1/2.8.0/2.9.0 FakeQuantWithMinMaxVars min/max assertion

Summaryinfo

A vulnerability marked as problematic has been reported in Google TensorFlow up to 2.7.1/2.8.0/2.9.0. Affected by this issue is the function FakeQuantWithMinMaxVars. This manipulation of the argument min/max causes assertion. This vulnerability is handled as CVE-2022-35971. The attack can be initiated remotely. There is not any exploit available. It is suggested to upgrade the affected component.

Detailsinfo

A vulnerability classified as problematic was found in Google TensorFlow up to 2.7.1/2.8.0/2.9.0 (Artificial Intelligence Software). Affected by this vulnerability is the function FakeQuantWithMinMaxVars. The manipulation of the argument min/max with an unknown input leads to a assertion vulnerability. The CWE definition for the vulnerability is 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. As an impact it is known to affect availability. The summary by CVE is:

TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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-9fpg-838v-wpv7. It is possible to read the advisory at github.com. This vulnerability is known as CVE-2022-35971 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 785d67a78a1d533759fcd2f5e8d6ef778de849e0 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
• 2.7.0
• 2.7.1
• 2.8
• 2.8.0
• 2.9.0

License

• free

Website

• Vendor: https://www.google.com/

CPE 2.3info

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CPE 2.2info

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