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Security Advisories: MDE2OlNlY3VyaXR5QWR2aXNvcnlHSFNBLXFjNTMtNDRjai12ZnZ4
Denial of Service in Tensorflow
Impact
The SparseCountSparseOutput
implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices
tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L185
However, malicious users can pass in tensors of different rank, resulting in a CHECK
assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor.
Patches
We have patched the issue in 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and will release a patch release.
We recommend users to upgrade to TensorFlow 2.3.1.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability is a variant of GHSA-p5f8-gfw5-33w4
Permalink: https://github.com/advisories/GHSA-qc53-44cj-vfvxJSON: https://advisories.ecosyste.ms/api/v1/advisories/MDE2OlNlY3VyaXR5QWR2aXNvcnlHSFNBLXFjNTMtNDRjai12ZnZ4
Source: GitHub Advisory Database
Origin: Unspecified
Severity: Moderate
Classification: General
Published: about 4 years ago
Updated: 15 days ago
CVSS Score: 6.3
CVSS vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:N/I:N/A:H
Identifiers: GHSA-qc53-44cj-vfvx, CVE-2020-15197
References:
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qc53-44cj-vfvx
- https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://nvd.nist.gov/vuln/detail/CVE-2020-15197
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-277.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-312.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-120.yaml
- https://github.com/advisories/GHSA-qc53-44cj-vfvx
Blast Radius: 30.7
Affected Packages
pypi:tensorflow-gpu
Dependent packages: 155Dependent repositories: 11,499
Downloads: 430,308 last month
Affected Version Ranges: = 2.3.0
Fixed in: 2.3.1
All affected versions:
All unaffected 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, 2.5.3, 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: 88Dependent repositories: 2,483
Downloads: 948,316 last month
Affected Version Ranges: = 2.3.0
Fixed in: 2.3.1
All affected versions:
All unaffected 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, 2.5.3, 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, 2.16.2, 2.17.0, 2.17.1, 2.18.0
pypi:tensorflow
Dependent packages: 2,172Dependent repositories: 73,755
Downloads: 18,843,694 last month
Affected Version Ranges: = 2.3.0
Fixed in: 2.3.1
All affected versions:
All unaffected 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, 2.5.3, 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, 2.16.2, 2.17.0, 2.17.1, 2.18.0