CVE-2022-23579: `CHECK`-failures during Grappler's `SafeToRemoveIdentity` in Tensorflow
First published: Fri Feb 04 2022(Updated: )
### Impact The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a `SavedModel` such that [`SafeToRemoveIdentity`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/dependency_optimizer.cc#L59-L98) would trigger `CHECK` failures. ### Patches We have patched the issue in GitHub commit [92dba16749fae36c246bec3f9ba474d9ddeb7662](https://github.com/tensorflow/tensorflow/commit/92dba16749fae36c246bec3f9ba474d9ddeb7662). 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 |
|---|---|---|
| Google TensorFlow | <=2.5.2 | |
| Google TensorFlow | >=2.6.0<=2.6.2 | |
| Google TensorFlow | =2.7.0 | |
| 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 |
| <=2.5.2 | ||
| >=2.6.0<=2.6.2 | ||
| =2.7.0 |
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Reference Links
- https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/dependency_optimizer.cc#L59-L98
- https://github.com/tensorflow/tensorflow/commit/92dba16749fae36c246bec3f9ba474d9ddeb7662
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5f2r-qp73-37mr
- https://nvd.nist.gov/vuln/detail/CVE-2022-23579
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-88.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-143.yaml
- https://github.com/advisories/GHSA-5f2r-qp73-37mr (Advisory)
Frequently Asked Questions
What is the severity of CVE-2022-23579?
CVE-2022-23579 has a severity rating of medium due to its potential to cause denial of service.
How do I fix CVE-2022-23579?
To remediate CVE-2022-23579, upgrade TensorFlow to version 2.7.1 or later.
Which versions of TensorFlow are affected by CVE-2022-23579?
CVE-2022-23579 affects TensorFlow versions up to 2.5.2 and specific versions from 2.6.0 to 2.6.2, as well as version 2.7.0.
What kind of attack does CVE-2022-23579 facilitate?
CVE-2022-23579 facilitates a denial of service attack by manipulating a SavedModel within TensorFlow.
What components of TensorFlow are impacted by CVE-2022-23579?
The Grappler optimizer component of TensorFlow is impacted by CVE-2022-23579.
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