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CVE-2021-29580
Good to know:
Date: May 14, 2021
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.
Language: Python
Severity Score
Related Resources (8)
Severity Score
Weakness Type (CWE)
Use of Uninitialized Resource
CWE-908Top Fix
CVSS v3.1
Base Score: |
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Attack Vector (AV): | LOCAL |
Attack Complexity (AC): | HIGH |
Privileges Required (PR): | LOW |
User Interaction (UI): | NONE |
Scope (S): | UNCHANGED |
Confidentiality (C): | NONE |
Integrity (I): | NONE |
Availability (A): | LOW |
CVSS v2
Base Score: |
|
---|---|
Access Vector (AV): | LOCAL |
Access Complexity (AC): | LOW |
Authentication (AU): | NONE |
Confidentiality (C): | NONE |
Integrity (I): | NONE |
Availability (A): | PARTIAL |
Additional information: |