CVE-2022-23567: Integer overflows in Tensorflow
First published: Thu Feb 03 2022(Updated: )
### Impact The [implementations of `Sparse*Cwise*` ops](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc) are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service): ```python import tensorflow as tf import numpy as np tf.raw_ops.SparseDenseCwiseDiv( sp_indices=np.array([[9]]), sp_values=np.array([5]), sp_shape=np.array([92233720368., 92233720368]), dense=np.array([4])) ``` We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The latter is an instance of [TFSA-2021-198](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md) (CVE-2021-41197) and is easily fixed by replacing a call to `TensorShape` constructor with a call to `BuildTensorShape` static helper factory. ### Patches We have patched the issue in GitHub commits [1b54cadd19391b60b6fcccd8d076426f7221d5e8](https://github.com/tensorflow/tensorflow/commit/1b54cadd19391b60b6fcccd8d076426f7221d5e8) and [e952a89b7026b98fe8cbe626514a93ed68b7c510](https://github.com/tensorflow/tensorflow/commit/e952a89b7026b98fe8cbe626514a93ed68b7c510). 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. ### Attribution This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.
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 |
Remedy
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md
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Reference Links
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc
- https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md
- https://github.com/tensorflow/tensorflow/commit/1b54cadd19391b60b6fcccd8d076426f7221d5e8
- https://github.com/tensorflow/tensorflow/commit/e952a89b7026b98fe8cbe626514a93ed68b7c510
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrx2-r989-2c43
- https://nvd.nist.gov/vuln/detail/CVE-2022-23567
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-76.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-131.yaml
- https://github.com/advisories/GHSA-rrx2-r989-2c43 (Advisory)
Frequently Asked Questions
What is the severity of CVE-2022-23567?
The severity of CVE-2022-23567 is considered high due to potential integer overflows that can lead to large allocation issues.
How do I fix CVE-2022-23567?
To fix CVE-2022-23567, update affected TensorFlow packages to version 2.7.1 or later for both CPU and GPU versions.
Which versions of TensorFlow are affected by CVE-2022-23567?
Affected versions of TensorFlow include 2.5.0 to 2.7.0, specifically 2.5.0, 2.6.0, and 2.7.0.
What types of TensorFlow packages are impacted by CVE-2022-23567?
CVE-2022-23567 impacts tensorflow-gpu, tensorflow-cpu, and tensorflow packages.
Can CVE-2022-23567 lead to denial of service attacks?
Yes, CVE-2022-23567 can lead to denial of service conditions due to large memory allocations triggered by integer overflows.
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