Summaryinfo

A vulnerability classified as problematic has been found in Google TensorFlow up to 2.7.1/2.8.0/2.9.0. This vulnerability affects the function QuantizedMatMul. Performing a manipulation of the argument min_a/max_a/min_b/max_b results in denial of service. This vulnerability was named CVE-2022-35973. The attack may be initiated remotely. There is no available exploit. It is recommended to upgrade the affected component. Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Detailsinfo

A vulnerability, which was classified as problematic, was found in Google TensorFlow up to 2.7.1/2.8.0/2.9.0 (Artificial Intelligence Software). This affects the function QuantizedMatMul. The manipulation of the argument min_a/max_a/min_b/max_b with an unknown input leads to a denial of service vulnerability. CWE is classifying the issue as CWE-404. The product does not release or incorrectly releases a resource before it is made available for re-use. This is going to have an impact on availability. The summary by CVE is:

TensorFlow is an open source platform for machine learning. If `QuantizedMatMul` is given nonscalar input for: `min_a`, `max_a`, `min_b`, or `max_b` It gives a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. 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 presented 09/17/2022 as GHSA-689c-r7h2-fv9v. The advisory is shared at github.com. This vulnerability is uniquely identified as CVE-2022-35973 since 07/15/2022. Technical details are known, but no exploit is available. MITRE ATT&CK project uses the attack technique T1499 for this issue.

Upgrading to version 2.7.2, 2.8.1, 2.9.1 or 2.10.0 eliminates this vulnerability. Applying the patch aca766ac7693bf29ed0df55ad6bfcc78f35e7f48 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.

Statistical analysis made it clear that VulDB provides the best quality 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

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• 🔍
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CPE 2.2info

• 🔍
• 🔍
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