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Security Advisories: MDE2OlNlY3VyaXR5QWR2aXNvcnlHSFNBLW02NDgtMzNxZi12M2dw

CHECK-fail in LSTM with zero-length input in TensorFlow

Impact

Running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend.

This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer.

Patches

We have patched the issue in GitHub commit 14755416e364f17fb1870882fa778c7fec7f16e3 and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.

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-m648-33qf-v3gp
JSON: https://advisories.ecosyste.ms/api/v1/advisories/MDE2OlNlY3VyaXR5QWR2aXNvcnlHSFNBLW02NDgtMzNxZi12M2dw
Source: GitHub Advisory Database
Origin: Unspecified
Severity: Low
Classification: General
Published: over 3 years ago
Updated: over 1 year ago


CVSS Score: 4.4
CVSS vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L

Identifiers: GHSA-m648-33qf-v3gp, CVE-2020-26270
References: Repository: https://github.com/tensorflow/tensorflow
Blast Radius: 21.4

Affected Packages

pypi:tensorflow-gpu
Dependent packages: 155
Dependent repositories: 11,499
Downloads: 297,977 last month
Affected Version Ranges: >= 2.3.0, < 2.3.2, >= 2.2.0, < 2.2.2, >= 2.1.0, < 2.1.3, >= 2.0.0, < 2.0.4, < 1.15.5
Fixed in: 2.3.2, 2.2.2, 2.1.3, 2.0.4, 1.15.5
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, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.1.0, 2.1.1, 2.1.2, 2.2.0, 2.2.1, 2.3.0, 2.3.1
All unaffected versions: 1.15.5, 2.0.4, 2.1.3, 2.1.4, 2.2.2, 2.2.3, 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, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0, 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: 88
Dependent repositories: 2,483
Downloads: 1,124,768 last month
Affected Version Ranges: >= 2.3.0, < 2.3.2, >= 2.2.0, < 2.2.2, >= 2.1.0, < 2.1.3, >= 2.0.0, < 2.0.4, < 1.15.5
Fixed in: 2.3.2, 2.2.2, 2.1.3, 2.0.4, 1.15.5
All affected versions: 1.15.0, 2.1.0, 2.1.1, 2.1.2, 2.2.0, 2.2.1, 2.3.0, 2.3.1
All unaffected versions: 2.1.3, 2.1.4, 2.2.2, 2.2.3, 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, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0, 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: 2,172
Dependent repositories: 73,755
Downloads: 22,714,121 last month
Affected Version Ranges: >= 2.3.0, < 2.3.2, >= 2.2.0, < 2.2.2, >= 2.1.0, < 2.1.3, >= 2.0.0, < 2.0.4, < 1.15.5
Fixed in: 2.3.2, 2.2.2, 2.1.3, 2.0.4, 1.15.5
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, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.1.0, 2.1.1, 2.1.2, 2.2.0, 2.2.1, 2.3.0, 2.3.1
All unaffected versions: 1.15.5, 2.0.4, 2.1.3, 2.1.4, 2.2.2, 2.2.3, 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, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0, 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