TensorFlow 2.11: SdcaOptimizer Rank Check Failure (CVE-2022-41899)
CVE-2022-41899 Published on November 18, 2022
`CHECK` fail via inputs in `SdcaOptimizer` in Tensorflow
TensorFlow is an open source platform for machine learning. Inputs `dense_features` or `example_state_data` not of rank 2 will trigger a `CHECK` fail in `SdcaOptimizer`. We have patched the issue in GitHub commit 80ff197d03db2a70c6a111f97dcdacad1b0babfa. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
Vulnerability Analysis
CVE-2022-41899 can be exploited with network access, requires user interaction and a small amount of user privileges. This vulnerability is consided to have a high level of attack complexity. Public availability of a proof of concept (POC) exploit exists for CVE-2022-41899. The potential impact of an exploit of this vulnerability is considered to have no impact on confidentiality and integrity, and a high impact on availability.
Weakness Type
Improper Input Validation
The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.
Products Associated with CVE-2022-41899
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Affected Versions
tensorflow:- Version >= 2.10.0, < 2.10.1 is affected.
- Version >= 2.9.0, < 2.9.3 is affected.
- Version < 2.8.4 is affected.
Vulnerable Packages
The following package name and versions may be associated with CVE-2022-41899
| Package Manager | Vulnerable Package | Versions | Fixed In |
|---|---|---|---|
| pip | tensorflow | < 2.8.4 | 2.8.4 |
| pip | tensorflow | >= 2.9.0, < 2.9.3 | 2.9.3 |
| pip | tensorflow | >= 2.10.0, < 2.10.1 | 2.10.1 |
| pip | tensorflow-cpu | < 2.8.4 | 2.8.4 |
| pip | tensorflow-gpu | < 2.8.4 | 2.8.4 |
| pip | tensorflow-cpu | >= 2.9.0, < 2.9.3 | 2.9.3 |
| pip | tensorflow-gpu | >= 2.9.0, < 2.9.3 | 2.9.3 |
| pip | tensorflow-cpu | >= 2.10.0, < 2.10.1 | 2.10.1 |
| pip | tensorflow-gpu | >= 2.10.0, < 2.10.1 | 2.10.1 |
Exploit Probability
EPSS (Exploit Prediction Scoring System) scores estimate the probability that a vulnerability will be exploited in the wild within the next 30 days. The percentile shows you how this score compares to all other vulnerabilities.