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Security Advisories: MDE2OlNlY3VyaXR5QWR2aXNvcnlHSFNBLWhjNmMtNzVwNC1obXE0

Reference binding to null pointer in `MatrixDiag*` ops

Impact

The implementation of MatrixDiag* operations does not validate that the tensor arguments are non-empty:

      num_rows = context->input(2).flat<int32>()(0);
      num_cols = context->input(3).flat<int32>()(0);
      padding_value = context->input(4).flat<T>()(0); 

Thus, users can trigger null pointer dereferences if any of the above tensors are null:

import tensorflow as tf

d = tf.convert_to_tensor([],dtype=tf.float32)
p = tf.convert_to_tensor([],dtype=tf.float32)
tf.raw_ops.MatrixDiagV2(diagonal=d, k=0, num_rows=0, num_cols=0, padding_value=p)

Changing from tf.raw_ops.MatrixDiagV2 to tf.raw_ops.MatrixDiagV3 still reproduces the issue.

Patches

We have patched the issue in GitHub commit a7116dd3913c4a4afd2a3a938573aa7c785fdfc6.

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.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by Ye Zhang and Yakun Zhang of Baidu X-Team.

Permalink: https://github.com/advisories/GHSA-hc6c-75p4-hmq4
JSON: https://advisories.ecosyste.ms/api/v1/advisories/MDE2OlNlY3VyaXR5QWR2aXNvcnlHSFNBLWhjNmMtNzVwNC1obXE0
Source: GitHub Advisory Database
Origin: Unspecified
Severity: Low
Classification: General
Published: about 2 years ago
Updated: 4 months ago


CVSS Score: 2.5
CVSS vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

Identifiers: GHSA-hc6c-75p4-hmq4, CVE-2021-29515
References:

Affected Packages

pypi:tensorflow-gpu
Versions: >= 2.4.0, < 2.4.2, >= 2.3.0, < 2.3.3, >= 2.2.0, < 2.2.3, < 2.1.4
Fixed in: 2.4.2, 2.3.3, 2.2.3, 2.1.4
pypi:tensorflow-cpu
Versions: >= 2.4.0, < 2.4.2, >= 2.3.0, < 2.3.3, >= 2.2.0, < 2.2.3, < 2.1.4
Fixed in: 2.4.2, 2.3.3, 2.2.3, 2.1.4
pypi:tensorflow
Versions: >= 2.4.0, < 2.4.2, >= 2.3.0, < 2.3.3, >= 2.2.0, < 2.2.3, < 2.1.4
Fixed in: 2.4.2, 2.3.3, 2.2.3, 2.1.4