PyPi: Tensorflow

CVE-2022-21731

Safety vulnerability ID: 44783

This vulnerability was reviewed by experts

The information on this page was manually curated by our Cybersecurity Intelligence Team.

Created at Feb 03, 2022 Updated at Jun 18, 2024
Scan your Python projects for vulnerabilities →

Advisory

Tensorflow versions 2.5.3, 2.6.3, 2.7.1 and 2.8.0 include a fix for CVE-2022-21731: 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.
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m4hf-j54p-p353

Affected package

tensorflow

Latest version: 2.16.1

TensorFlow is an open source machine learning framework for everyone.

Affected versions

Fixed versions

Vulnerability changelog

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. See CVE-2022-21731.


CONFIRM:https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m4hf-j54p-p353: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m4hf-j54p-p353
MISC:https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/common_shape_fns.cc#L1961-L2059: https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/common_shape_fns.cc#L1961-L2059
MISC:https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.cc#L345-L358: https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.cc#L345-L358
MISC:https://github.com/tensorflow/tensorflow/commit/08d7b00c0a5a20926363849f611729f53f3ec022: https://github.com/tensorflow/tensorflow/commit/08d7b00c0a5a20926363849f611729f53f3ec022

Resources

Use this package?

Scan your Python project for dependency vulnerabilities in two minutes

Scan your application

Severity Details

CVSS Base Score

MEDIUM 6.5

CVSS v3 Details

MEDIUM 6.5
Attack Vector (AV)
NETWORK
Attack Complexity (AC)
LOW
Privileges Required (PR)
LOW
User Interaction (UI)
NONE
Scope (S)
UNCHANGED
Confidentiality Impact (C)
NONE
Integrity Impact (I)
NONE
Availability Availability (A)
HIGH

CVSS v2 Details

MEDIUM 4.0
Access Vector (AV)
NETWORK
Access Complexity (AC)
LOW
Authentication (Au)
SINGLE
Confidentiality Impact (C)
NONE
Integrity Impact (I)
NONE
Availability Impact (A)
PARTIAL