CVE-2020-15197: Denial of Service in Tensorflow
First published: Fri Sep 25 2020(Updated: )
### 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](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-p5f8-gfw5-33w4](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4)
Credit: security-advisories@github.com security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| Google TensorFlow | =2.3.0 | |
| pip/tensorflow-gpu | =2.3.0 | 2.3.1 |
| pip/tensorflow-cpu | =2.3.0 | 2.3.1 |
| pip/tensorflow | =2.3.0 | 2.3.1 |
| =2.3.0 |
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Reference Links
- https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qc53-44cj-vfvx
- 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 (Advisory)
Frequently Asked Questions
What is the vulnerability ID of this security flaw?
The vulnerability ID is CVE-2020-15197.
What is the severity level of CVE-2020-15197?
The severity level of CVE-2020-15197 is medium with a score of 6.3.
Which version of Tensorflow is affected by this vulnerability?
Tensorflow version 2.3.0 is affected by this vulnerability.
How can I fix this vulnerability?
To fix this vulnerability, update Tensorflow to version 2.3.1 or later.
Are there any references related to this vulnerability?
Yes, you can find references related to this vulnerability at the following links: [Link 1](https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02), [Link 2](https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1), [Link 3](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qc53-44cj-vfvx)
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