Vulnerability · Published Feb 3, 2022 · Assigned by GitHub_M
CVE-2022-21731Type confusion leading to segfault in Tensorflow
Medium 6.5
In plain English
A medium-severity type confusion in the tensorflow package (PyPI). Proof-of-concept exploit code is public. The chance it is exploited in the next 30 days is estimated at 0.9% (higher than 58% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.
Official 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.
Affected packages & fixed versions
| Ecosystem | Package | Fixed in | Advisory |
|---|---|---|---|
| PyPI | tensorflow | 2.5.3 | GHSA-m4hf-j54p-p353 |
| PyPI | tensorflow | 2.6.3 | GHSA-m4hf-j54p-p353 |
| PyPI | tensorflow | 2.7.1 | GHSA-m4hf-j54p-p353 |
| PyPI | tensorflow | 2.5.3, 2.6.3, 2.7.1 | PYSEC-2026-3211 |
| PyPI | tensorflow-cpu | 2.6.3 | GHSA-m4hf-j54p-p353 |
| PyPI | tensorflow-cpu | 2.7.1 | GHSA-m4hf-j54p-p353 |
| PyPI | tensorflow-cpu | 2.5.3, 2.6.3 | PYSEC-2022-55 |
| PyPI | tensorflow-cpu | 2.5.3 | GHSA-m4hf-j54p-p353 |
| PyPI | tensorflow-gpu | 2.7.1 | GHSA-m4hf-j54p-p353 |
| PyPI | tensorflow-gpu | 2.5.3, 2.6.3 | PYSEC-2022-110 |
| PyPI | tensorflow-gpu | 2.5.3 | GHSA-m4hf-j54p-p353 |
| PyPI | tensorflow-gpu | 2.6.3 | GHSA-m4hf-j54p-p353 |
Affected products (as reported)
Weakness: CWE-843 · Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m4hf-j54p-p353 x_refsource_CONFIRM
- https://github.com/tensorflow/tensorflow/commit/08d7b00c0a5a20926363849f611729f53f3ec022 x_refsource_MISC
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/common_shape_fns.cc#L1961-L2059 x_refsource_MISC
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.cc#L345-L358 x_refsource_MISC