CVE-2020-15194: Denial of Service in Tensorflow
First published: Fri Sep 25 2020(Updated: )
### Impact The `SparseFillEmptyRowsGrad` implementation has incomplete validation of the shapes of its arguments: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L235-L241 Although `reverse_index_map_t` and `grad_values_t` are accessed in a similar pattern, only `reverse_index_map_t` is validated to be of proper shape. Hence, malicious users can pass a bad `grad_values_t` to trigger an assertion failure in `vec`, causing denial of service in serving installations. ### Patches We have patched the issue in 390611e0d45c5793c7066110af37c8514e6a6c54 and will release a patch release for all affected versions. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability is a variant of [GHSA-63xm-rx5p-xvqr](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-63xm-rx5p-xvqr)
Credit: security-advisories@github.com security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| pip/tensorflow-gpu | =2.3.0 | 2.3.1 |
| pip/tensorflow-gpu | =2.2.0 | 2.2.1 |
| pip/tensorflow-gpu | >=2.1.0<2.1.2 | 2.1.2 |
| pip/tensorflow-gpu | >=2.0.0<2.0.3 | 2.0.3 |
| pip/tensorflow-gpu | <1.15.4 | 1.15.4 |
| pip/tensorflow-cpu | =2.3.0 | 2.3.1 |
| pip/tensorflow-cpu | =2.2.0 | 2.2.1 |
| pip/tensorflow-cpu | >=2.1.0<2.1.2 | 2.1.2 |
| pip/tensorflow-cpu | >=2.0.0<2.0.3 | 2.0.3 |
| pip/tensorflow-cpu | <1.15.4 | 1.15.4 |
| pip/tensorflow | =2.3.0 | 2.3.1 |
| pip/tensorflow | =2.2.0 | 2.2.1 |
| pip/tensorflow | >=2.1.0<2.1.2 | 2.1.2 |
| pip/tensorflow | >=2.0.0<2.0.3 | 2.0.3 |
| pip/tensorflow | <1.15.4 | 1.15.4 |
| TensorFlow Keras | <1.15.4 | |
| TensorFlow Keras | >=2.0.0<2.0.3 | |
| TensorFlow Keras | >=2.1.0<2.1.2 | |
| TensorFlow Keras | >=2.2.0<2.2.1 | |
| TensorFlow Keras | >=2.3.0<2.3.1 | |
| SUSE Linux | =15.2 |
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Reference Links
- http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html
- https://github.com/tensorflow/tensorflow/commit/390611e0d45c5793c7066110af37c8514e6a6c54
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9mqp-7v2h-2382
- https://nvd.nist.gov/vuln/detail/CVE-2020-15194
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-274.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-309.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-117.yaml
- https://github.com/advisories/GHSA-9mqp-7v2h-2382 (Advisory)
Frequently Asked Questions
What is the severity of CVE-2020-15194?
CVE-2020-15194 has been classified as a medium severity vulnerability due to incomplete validation of argument shapes.
How do I fix CVE-2020-15194?
To fix CVE-2020-15194, upgrade to TensorFlow version 2.3.1 or higher.
Which versions of TensorFlow are affected by CVE-2020-15194?
CVE-2020-15194 affects TensorFlow versions 1.15.4 and the 2.x series up to and including 2.3.0.
Is CVE-2020-15194 specific to TensorFlow GPU or CPU versions?
CVE-2020-15194 impacts both TensorFlow GPU and CPU versions.
Where can I find the commit related to CVE-2020-15194?
The commit related to CVE-2020-15194 can be found within the TensorFlow GitHub repository.
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