CVE-2021-29580
The code is also vulnerable to a denial of service attack as a `CHECK` condition becomes false and aborts the process.
Does this matter?
Lower severity and a low EPSS score (0.19%). Track it; it rarely justifies an emergency change on its own.
Description
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a `CHECK` condition becomes false and aborts the process. The implementation(https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
- CVSS 3.1
- 5.5 MEDIUMCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- EPSS
- 0.19% probability · 9th percentile
- CISA KEV
- Not listed
- Weakness
- CWE-908
- Affected
- google/tensorflow
- Source
- security-advisories@github.com
References
- https://github.com/tensorflow/tensorflow/commit/32fdcbff9d06d010d908fcc4bd4b36eb3ce15925Patch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgpExploit, Patch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/commit/32fdcbff9d06d010d908fcc4bd4b36eb3ce15925Patch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgpExploit, Patch, Third Party Advisory
Source: NVD record, EPSS from FIRST.org, KEV from CISA. Refreshed daily.