CVE-2020-15199: Denial of Service in Tensorflow
First published: Fri Sep 25 2020(Updated: )
### Impact The `RaggedCountSparseOutput` does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the `splits` tensor has the minimum required number of elements. Code uses this quantity to initialize a different data structure: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L241-L244 Since `BatchedMap` is equivalent to a vector, it needs to have at least one element to not be `nullptr`. If user passes a `splits` tensor that is empty or has exactly one element, we get a `SIGABRT` signal raised by the operating system. ### 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-x5cp-9pcf-pp3h
- https://nvd.nist.gov/vuln/detail/CVE-2020-15199
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-279.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-314.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-122.yaml
- https://github.com/advisories/GHSA-x5cp-9pcf-pp3h (Advisory)
Frequently Asked Questions
What is the severity of CVE-2020-15199?
CVE-2020-15199 is rated as a moderate vulnerability due to improper input validation in TensorFlow.
How do I fix CVE-2020-15199?
Upgrade to TensorFlow version 2.3.1 or later to resolve CVE-2020-15199.
What software versions are affected by CVE-2020-15199?
CVE-2020-15199 affects TensorFlow version 2.3.0 across all its distributions including tensorflow-gpu and tensorflow-cpu.
What happens if I do not address CVE-2020-15199?
Failure to address CVE-2020-15199 may allow unauthorized manipulation of tensors, potentially leading to unexpected application behavior.
How can I verify if I am using a vulnerable version related to CVE-2020-15199?
Check your TensorFlow installation with the command 'pip show tensorflow' to see if it's version 2.3.0.
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