CVE-2022-23576: Integer overflow in Tensorflow
First published: Fri Feb 04 2022(Updated: )
### Impact The [implementation of `OpLevelCostEstimator::CalculateOutputSize`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1598-L1617) is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements: ```cc for (const auto& dim : output_shape.dim()) { output_size *= dim.size(); } ``` Here, we can have a large enough number of dimensions in `output_shape.dim()` or just a small number of dimensions being large enough to cause an overflow in the multiplication. ### Patches We have patched the issue in GitHub commit [b9bd6cfd1c50e6807846af9a86f9b83cafc9c8ae](https://github.com/tensorflow/tensorflow/commit/b9bd6cfd1c50e6807846af9a86f9b83cafc9c8ae). The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. ### 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.
Credit: security-advisories@github.com security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| pip/tensorflow-gpu | =2.7.0 | 2.7.1 |
| pip/tensorflow-gpu | >=2.6.0<2.6.3 | 2.6.3 |
| pip/tensorflow-gpu | <2.5.3 | 2.5.3 |
| pip/tensorflow-cpu | =2.7.0 | 2.7.1 |
| pip/tensorflow-cpu | >=2.6.0<2.6.3 | 2.6.3 |
| pip/tensorflow-cpu | <2.5.3 | 2.5.3 |
| pip/tensorflow | =2.7.0 | 2.7.1 |
| pip/tensorflow | >=2.6.0<2.6.3 | 2.6.3 |
| pip/tensorflow | <2.5.3 | 2.5.3 |
| TensorFlow Keras | <=2.5.2 | |
| TensorFlow Keras | >=2.6.0<=2.6.2 | |
| TensorFlow Keras | =2.7.0 |
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Reference Links
- https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1598-L1617
- https://github.com/tensorflow/tensorflow/commit/b9bd6cfd1c50e6807846af9a86f9b83cafc9c8ae
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wm93-f238-7v37
- https://nvd.nist.gov/vuln/detail/CVE-2022-23576
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-85.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-140.yaml
- https://github.com/advisories/GHSA-wm93-f238-7v37 (Advisory)
Frequently Asked Questions
What is the severity of CVE-2022-23576?
CVE-2022-23576 is rated as high severity due to the integer overflow vulnerability that can lead to denial of service.
How do I fix CVE-2022-23576?
To remediate CVE-2022-23576, upgrade to TensorFlow version 2.7.1 or later.
Which versions of TensorFlow are affected by CVE-2022-23576?
CVE-2022-23576 affects TensorFlow versions up to 2.5.2, versions 2.6.0 to 2.6.2, and version 2.7.0.
What component of TensorFlow is affected by CVE-2022-23576?
The vulnerability in CVE-2022-23576 affects the OpLevelCostEstimator component in TensorFlow.
Can CVE-2022-23576 lead to remote code execution?
No, CVE-2022-23576 primarily leads to denial of service rather than remote code execution.
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