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GHSA-rg3m-hqc5-344v

HighCVSS 7.1 / 10
Published Nov 10, 2021·Last modified Mar 13, 2026
Affected Components(0)

No affected components available

Description

Impact

The implementation of SparseFillEmptyRows can be made to trigger a heap OOB access:

import tensorflow as tf
  
data=tf.raw_ops.SparseFillEmptyRows(
  indices=[[0,0],[0,0],[0,0]],
  values=['sssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssss'],
  dense_shape=[5,3],
  default_value='o')

This occurs whenever the size of indices does not match the size of values.

Patches

We have patched the issue in GitHub commit 67bfd9feeecfb3c61d80f0e46d89c170fbee682b.

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 members of the Aivul Team from Qihoo 360.

Risk Scores
Base Score
7.1

The vulnerability requires local access to the device to be exploited. It is easy for an attacker to exploit this vulnerability. An attacker needs basic access or low-level privileges. No user interaction is needed for the attacker to exploit this vulnerability. The impact is confined to the system where the vulnerability exists. There is a high impact on the confidentiality of the information. There is a high impact on the availability of the system.

Threat Intelligence
6.5

Exploitation attempts have been detected. Elevated vigilance and prompt remediation are advised.

EPSS
0.20%

The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.

Exploit
Not available

We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.

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High severity
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