CVE-2021-29583 Information

Description

TensorFlow is an end-to-end open source platform for machine learning. The implementation of tf.raw_ops.FusedBatchNorm is vulnerable to a heap buffer overflow. If the tensors are empty the same implementation can trigger undefined behavior by dereferencing null pointers. The implementation(https://github.com/tensorflow/tensorflow/blob/57d86e0db5d1365f19adcce848dfc1bf89fdd4c7/tensorflow/core/kernels/fused_batch_norm_op.cc) fails to validate that scale offset mean and variance (the last two only when required) all have the same number of elements as the number of channels of x. This results in heap out of bounds reads when the buffers backing these tensors are indexed past their boundary. If the tensors are empty the validation mentioned in the above paragraph would also trigger and prevent the undefined behavior. 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 Vector

CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Reference

https://github.com/tensorflow/tensorflow/commit/6972f9dfe325636b3db4e0bc517ee22a159365c0 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9xh4-23q4-v6wr

Attack Complexity

LOW

Privileges Required

LOW

User Interaction Required

LOW

Scope

NONE

Confidentiality Impact

UNCHANGED

Integrity Impact

HIGH

Availability Impact

HIGH

Base Score

HIGH

Base Severity

7.8