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CVE-2022-35974

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Date: September 16, 2022

TensorFlow is an open source platform for machine learning. If `QuantizeDownAndShrinkRange` is given nonscalar inputs for `input_min` or `input_max`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 73ad1815ebcfeb7c051f9c2f7ab5024380ca8613. 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.

Language: Python

Severity Score

Related Resources (4)

https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vgvh-2pf4-jr2x
https://github.com/tensorflow/tensorflow/commit/73ad1815ebcfeb7c051f9c2f7ab5024380ca8613
https://nvd.nist.gov/vuln/detail/CVE-2022-35974
https://www.mend.io/vulnerability-database/CVE-2022-35974

Severity Score

Weakness Type (CWE)

Input Validation

CWE-20

Insufficient Information

NVD-CWE-noinfo

Top Fix

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Upgrade Version

Upgrade to version tensorflow - 2.7.2,2.8.1,2.9.1,2.10.0, tensorflow-cpu - 2.7.2,2.8.1,2.9.1,2.10.0, tensorflow-gpu - 2.7.2,2.8.1,2.9.1,2.10.0

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CVSS v3.1

Base Score:
Attack Vector (AV): NETWORK
Attack Complexity (AC): LOW
Privileges Required (PR): NONE
User Interaction (UI): NONE
Scope (S): UNCHANGED
Confidentiality (C): NONE
Integrity (I): NONE
Availability (A): HIGH

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