Vulnerability CVE-2021-29580


Published: 2021-05-14   Modified: 2021-05-15

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.

Type:

CWE-908

CVSS2 => (AV:L/AC:L/Au:N/C:N/I:N/A:P)

CVSS Base Score
Impact Subscore
Exploitability Subscore
2.1/10
2.9/10
3.9/10
Exploit range
Attack complexity
Authentication
Local
Low
No required
Confidentiality impact
Integrity impact
Availability impact
None
None
Partial
Affected software
Google -> Tensorflow 

 References:
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgp
https://github.com/tensorflow/tensorflow/commit/32fdcbff9d06d010d908fcc4bd4b36eb3ce15925

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