CVE-2022-21731
Description
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank. However, `WithRankAtLeast` receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that `min_rank` is a 32-bits value and the value of `axis`, the `rank` argument is a negative value, so the error check is bypassed. 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.
Predictions
Heuristic predictions, AS-IS, for prioritization only.
Mitigations
No mitigations published for this CVE yet.
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OS impact
Debian Fixed 2 releases
| Version | Status | Fixed in |
|---|---|---|
| sid | Fixed | 0 |
| forky | Fixed | 0 |
Package impact
| Ecosystem | Package | Vulnerable | Fixed |
|---|---|---|---|
| PyPI | tensorflow | <2.5.3 | 2.5.3 |
| PyPI | tensorflow | >=2.6.0,<2.6.3 | 2.6.3 |
| PyPI | tensorflow | >=2.7.0,<2.7.1 | 2.7.1 |
| PyPI | tensorflow-cpu | <2.5.3 | 2.5.3 |
| PyPI | tensorflow-cpu | >=2.6.0,<2.6.3 | 2.6.3 |
| PyPI | tensorflow-cpu | >=2.7.0,<2.7.1 | 2.7.1 |
| PyPI | tensorflow-gpu | <2.5.3 | 2.5.3 |
| PyPI | tensorflow-gpu | >=2.6.0,<2.6.3 | 2.6.3 |
| PyPI | tensorflow-gpu | >=2.7.0,<2.7.1 | 2.7.1 |
| PyPI | tensorflow-gpu | <08d7b00c0a5a20926363849f611729f53f3ec022||>=2.6.0,<2.6.3 | 08d7b00c0a5a20926363849f611729f53f3ec022 |
| PyPI | tensorflow-cpu | <08d7b00c0a5a20926363849f611729f53f3ec022||>=2.6.0,<2.6.3 | 08d7b00c0a5a20926363849f611729f53f3ec022 |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m4hf-j54p-p353
- https://nvd.nist.gov/vuln/detail/CVE-2022-21731
- https://github.com/tensorflow/tensorflow/commit/08d7b00c0a5a20926363849f611729f53f3ec022
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-55.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-110.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/common_shape_fns.cc#L1961-L2059
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.cc#L345-L358
- https://security-tracker.debian.org/tracker/CVE-2022-21731
Community-verified mitigations for this CVE will appear above when contributors publish them.
Verify integrity in audit chain (admin only). AS-IS.