CVE-2021-37650: Segfault and heap buffer overflow in `{Experimental,}DatasetToTFRecord` in TensorFlow

Published Aug 12, 2021
·
Updated

Impact The implementation for tf.rawops.ExperimentalDatasetToTFRecord and tf.rawops.DatasetToTFRecord can trigger heap buffer overflow and segmentation fault:

python import tensorflow as tf

dataset = tf.data.Dataset.range(3) dataset = tf.data.experimental.tovariant(dataset) tf.rawops.ExperimentalDatasetToTFRecord( inputdataset=dataset, filename='/tmp/output', compressiontype='')

The implementation assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types.

Patches We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876.

The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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.

Other sources

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for tf.rawops.ExperimentalDatasetToTFRecord and tf.rawops.DatasetToTFRecord can trigger heap buffer overflow and segmentation fault. The implementation assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types. We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Affected Software

15 affected componentsFixes available
pip/tensorflow-gpu=2.5.0
2.5.1
pip/tensorflow-gpu>=2.4.0<2.4.3
2.4.3
pip/tensorflow-gpu<2.3.4
2.3.4
pip/tensorflow-cpu=2.5.0
2.5.1
pip/tensorflow-cpu>=2.4.0<2.4.3
2.4.3
pip/tensorflow-cpu<2.3.4
2.3.4
pip/tensorflow=2.5.0
2.5.1
pip/tensorflow>=2.4.0<2.4.3
2.4.3
pip/tensorflow<2.3.4
2.3.4
Google TensorFlow>=2.3.0<2.3.4
Google TensorFlow>=2.4.0<2.4.3
Google TensorFlow=2.5.0
Google TensorFlow=2.6.0-rc0
Google TensorFlow=2.6.0-rc1
Google TensorFlow=2.6.0-rc2

Remediation

Recommended actions to resolve this vulnerability, in priority order.

  1. Upgrade

    Upgrade pip/tensorflow-gpu to a version that resolves this vulnerability.

    Fixed in 2.5.1
  2. Upgrade

    Upgrade pip/tensorflow-gpu to a version that resolves this vulnerability.

    Fixed in 2.4.3
  3. Upgrade

    Upgrade pip/tensorflow-gpu to a version that resolves this vulnerability.

    Fixed in 2.3.4
  4. Upgrade

    Upgrade pip/tensorflow-cpu to a version that resolves this vulnerability.

    Fixed in 2.5.1
  5. Upgrade

    Upgrade pip/tensorflow-cpu to a version that resolves this vulnerability.

    Fixed in 2.4.3
  6. Upgrade

    Upgrade pip/tensorflow-cpu to a version that resolves this vulnerability.

    Fixed in 2.3.4
  7. Upgrade

    Upgrade pip/tensorflow to a version that resolves this vulnerability.

    Fixed in 2.5.1
  8. Upgrade

    Upgrade pip/tensorflow to a version that resolves this vulnerability.

    Fixed in 2.4.3
  9. Upgrade

    Upgrade pip/tensorflow to a version that resolves this vulnerability.

    Fixed in 2.3.4
  10. Upgrade

    Upgrade tensorflow/tensorflow to a version that resolves this vulnerability.

    Fixed in 2.6.0Patch e0b6e58c328059829c3eb968136f17aa72b6c876
  11. Upgrade

    Upgrade tensorflow/tensorflow to a version that resolves this vulnerability.

    Fixed in 2.5.1Patch e0b6e58c328059829c3eb968136f17aa72b6c876
  12. Upgrade

    Upgrade tensorflow/tensorflow to a version that resolves this vulnerability.

    Fixed in 2.4.3Patch e0b6e58c328059829c3eb968136f17aa72b6c876
  13. Upgrade

    Upgrade tensorflow/tensorflow to a version that resolves this vulnerability.

    Fixed in 2.3.4Patch e0b6e58c328059829c3eb968136f17aa72b6c876

Event History

Aug 12, 2021
CVE Published
via MITRE·09:00 PM
Data Sourced
via MITRE·09:00 PM
DescriptionSeverityWeakness
Data Sourced
via NVD·09:15 PM
RemedyDescriptionSeverityWeaknessAffected Software
Aug 25, 2021
Advisory Published
via GitHub·02:43 PM

Frequently Asked Questions

1

What is the severity of CVE-2021-37650?

CVE-2021-37650 is categorized as a high severity vulnerability which can lead to heap buffer overflow and segmentation faults.

2

How do I fix CVE-2021-37650?

To fix CVE-2021-37650, update TensorFlow to versions 2.3.4, 2.4.3, or 2.5.1.

3

What are the affected TensorFlow versions for CVE-2021-37650?

CVE-2021-37650 affects TensorFlow versions 2.3.0 to 2.3.4, 2.4.0 to 2.4.3, and specific release candidates of 2.6.0.

4

What are the potential impacts of CVE-2021-37650?

Potential impacts of CVE-2021-37650 include application crashes and execution of arbitrary code due to memory corruption.

5

Is CVE-2021-37650 present in TensorFlow GPU packages?

Yes, CVE-2021-37650 is present in both TensorFlow CPU and GPU packages for the affected versions.

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