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CVE-2022-21731

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Date: February 3, 2022

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank. However, `WithRankAtLeast` receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that `min_rank` is a 32-bits value and the value of `axis`, the `rank` argument is a negative value, so the error check is bypassed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Language: Python

Severity Score

Severity Score

Weakness Type (CWE)

Access of Resource Using Incompatible Type ('Type Confusion')

CWE-843

Top Fix

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Upgrade Version

Upgrade to version tensorflow - 2.5.3,2.6.3,2.7.1;tensorflow-cpu - 2.5.3,2.6.3,2.7.1;tensorflow-gpu - 2.5.3,2.6.3,2.7.1

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CVSS v3.1

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

CVSS v2

Base Score:
Access Vector (AV): NETWORK
Access Complexity (AC): LOW
Authentication (AU): SINGLE
Confidentiality (C): NONE
Integrity (I): NONE
Availability (A): PARTIAL
Additional information:

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