Upstream information

CVE-2021-29583 at MITRE

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.

SUSE information

Overall state of this security issue: Does not affect SUSE products

This issue is currently rated as having moderate severity.

CVSS v2 Scores
  National Vulnerability Database
Base Score 4.6
Vector AV:L/AC:L/Au:N/C:P/I:P/A:P
Access Vector Local
Access Complexity Low
Authentication None
Confidentiality Impact Partial
Integrity Impact Partial
Availability Impact Partial
CVSS v3 Scores
  National Vulnerability Database
Base Score 7.8
Vector CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Access Vector Local
Access Complexity Low
Privileges Required Low
User Interaction None
Scope Unchanged
Confidentiality Impact High
Integrity Impact High
Availability Impact High
CVSSv3 Version 3.1
SUSE Bugzilla entry: 1186108 [NEW]

No SUSE Security Announcements cross referenced.