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CVE-2022-35967

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Date: September 16, 2022

TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. 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 (6)

https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v6h3-348g-6h5x
https://github.com/tensorflow/tensorflow/commit/49b3824d83af706df0ad07e4e677d88659756d89
https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0
https://nvd.nist.gov/vuln/detail/CVE-2022-35967
https://github.com/tensorflow/tensorflow
https://www.mend.io/vulnerability-database/CVE-2022-35967

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): HIGH
Privileges Required (PR): NONE
User Interaction (UI): NONE
Scope (S): UNCHANGED
Confidentiality (C): NONE
Integrity (I): NONE
Availability (A): HIGH

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