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Security Advisories: GSA_kwCzR0hTQS1qM21qLWZocHEtcXFqas0osQ
Reachable Assertion in Tensorflow
Impact
When decoding a tensor from protobuf, a TensorFlow process can encounter cases where a CHECK
assertion is invalidated based on user controlled arguments, if the tensors have an invalid dtype
and 0 elements or an invalid shape. This allows attackers to cause denial of services in TensorFlow processes.
Patches
We have patched the issue in GitHub commit 5b491cd5e41ad63735161cec9c2a568172c8b6a3.
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.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Permalink: https://github.com/advisories/GHSA-j3mj-fhpq-qqjjJSON: https://advisories.ecosyste.ms/api/v1/advisories/GSA_kwCzR0hTQS1qM21qLWZocHEtcXFqas0osQ
Source: GitHub Advisory Database
Origin: Unspecified
Severity: Moderate
Classification: General
Published: about 2 years ago
Updated: about 1 year ago
CVSS Score: 6.5
CVSS vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Identifiers: GHSA-j3mj-fhpq-qqjj, CVE-2022-23571
References:
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j3mj-fhpq-qqjj
- https://nvd.nist.gov/vuln/detail/CVE-2022-23571
- https://github.com/tensorflow/tensorflow/commit/5b491cd5e41ad63735161cec9c2a568172c8b6a3
- https://github.com/advisories/GHSA-j3mj-fhpq-qqjj
Blast Radius: 31.6
Affected Packages
pypi:tensorflow-gpu
Dependent packages: 146Dependent repositories: 11,499
Downloads: 354,712 last month
Affected Version Ranges: = 2.7.0, >= 2.6.0, < 2.6.3, < 2.5.3
Fixed in: 2.7.1, 2.6.3, 2.5.3
All affected versions: 0.12.0, 0.12.1, 1.0.0, 1.0.1, 1.1.0, 1.2.0, 1.2.1, 1.3.0, 1.4.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.7.0, 1.7.1, 1.8.0, 1.9.0, 1.10.0, 1.10.1, 1.11.0, 1.12.0, 1.12.2, 1.12.3, 1.13.1, 1.13.2, 1.14.0, 1.15.0, 1.15.2, 1.15.3, 1.15.4, 1.15.5, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.6.0, 2.6.1, 2.6.2, 2.7.0
All unaffected versions: 2.5.3, 2.6.3, 2.6.4, 2.6.5, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.0, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.12.0
pypi:tensorflow-cpu
Dependent packages: 71Dependent repositories: 2,483
Downloads: 942,065 last month
Affected Version Ranges: = 2.7.0, >= 2.6.0, < 2.6.3, < 2.5.3
Fixed in: 2.7.1, 2.6.3, 2.5.3
All affected versions: 1.15.0, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.6.0, 2.6.1, 2.6.2, 2.7.0
All unaffected versions: 2.5.3, 2.6.3, 2.6.4, 2.6.5, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.0, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.11.1, 2.12.0, 2.12.1, 2.13.0, 2.13.1, 2.14.0, 2.14.1, 2.15.0, 2.15.1, 2.16.1
pypi:tensorflow
Dependent packages: 1,733Dependent repositories: 73,755
Downloads: 22,560,575 last month
Affected Version Ranges: = 2.7.0, >= 2.6.0, < 2.6.3, < 2.5.3
Fixed in: 2.7.1, 2.6.3, 2.5.3
All affected versions: 0.12.0, 0.12.1, 1.0.0, 1.0.1, 1.1.0, 1.2.0, 1.2.1, 1.3.0, 1.4.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.7.0, 1.7.1, 1.8.0, 1.9.0, 1.10.0, 1.10.1, 1.11.0, 1.12.0, 1.12.2, 1.12.3, 1.13.1, 1.13.2, 1.14.0, 1.15.0, 1.15.2, 1.15.3, 1.15.4, 1.15.5, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.6.0, 2.6.1, 2.6.2, 2.7.0
All unaffected versions: 2.5.3, 2.6.3, 2.6.4, 2.6.5, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.0, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.11.1, 2.12.0, 2.12.1, 2.13.0, 2.13.1, 2.14.0, 2.14.1, 2.15.0, 2.15.1, 2.16.1