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GHSA-5hx2-qx8j-qjqm

MediumCVSS 5.5 / 10
Published Nov 10, 2021·Last modified Mar 13, 2026
Affected Components(0)

No affected components available

Description

Impact

If tf.image.resize is called with a large input argument then the TensorFlow process will crash due to a CHECK-failure caused by an overflow.

import tensorflow as tf
import numpy as np

tf.keras.layers.UpSampling2D(
  size=1610637938,
  data_format='channels_first',
  interpolation='bilinear')(np.ones((5,1,1,1)))

The number of elements in the output tensor is too much for the int64_t type and the overflow is detected via a CHECK statement. This aborts the process.

Patches

We have patched the issue in GitHub commit e5272d4204ff5b46136a1ef1204fc00597e21837 (merging #51497).

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 externally via a GitHub issue.

Risk Scores
Base Score
5.5

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 availability of the system.

Threat Intelligence
5.1

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

EPSS
0.23%

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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