CVE-2021-37688: Null pointer dereference in TensorFlow Lite

Published Aug 12, 2021
·
Updated

Impact An attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service:

python import tensorflow as tf

model = tf.keras.models.Sequential() model.add(tf.keras.Input(shape=(1, 2, 3))) model.add(tf.keras.layers.Dense(0, activation='relu'))

converter = tf.lite.TFLiteConverter.fromkerasmodel(model) tflitemodel = converter.convert()

interpreter = tf.lite.Interpreter(modelcontent=tflitemodel) interpreter.allocatetensors()

interpreter.invoke()

The implementation unconditionally dereferences a pointer.

cc if (y4 > 1) { // ... } else { for (int i0 = 0; i0 < y0; ++i0) { const T input2dataptr = nullptr; for (int i1 = 0; i1 < y1; ++i1) { input2dataptr = input2datareset; for (int i2 = 0; i2 < y2; ++i2) { scalarbroadcastf(y3, params, input1dataptr, input2dataptr, outputdataptr); } } } }

Patches We have patched the issue in GitHub commit 15691e456c7dc9bd6be203b09765b063bf4a380c.

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 Yakun Zhang of Baidu Security.

Other sources

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. The implementation unconditionally dereferences a pointer. We have patched the issue in GitHub commit 15691e456c7dc9bd6be203b09765b063bf4a380c. 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<2.3.4
2.3.4
pip/tensorflow-cpu>=2.4.0<2.4.3
2.4.3
pip/tensorflow-cpu=2.5.0
2.5.1
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 2.3.4
  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 2.5.1
  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 Lite (TensorFlow) to a version that resolves this vulnerability.

    Fixed in 2.6.0Patch 15691e456c7dc9bd6be203b09765b063bf4a380c
  11. Upgrade

    Upgrade TensorFlow Lite (TensorFlow) to a version that resolves this vulnerability.

    Fixed in 2.5.1Patch 15691e456c7dc9bd6be203b09765b063bf4a380c
  12. Upgrade

    Upgrade TensorFlow Lite (TensorFlow) to a version that resolves this vulnerability.

    Fixed in 2.4.3Patch 15691e456c7dc9bd6be203b09765b063bf4a380c
  13. Upgrade

    Upgrade TensorFlow Lite (TensorFlow) to a version that resolves this vulnerability.

    Fixed in 2.3.4Patch 15691e456c7dc9bd6be203b09765b063bf4a380c

Event History

Aug 12, 2021
CVE Published
via MITRE·10:00 PM
Data Sourced
via MITRE·10:00 PM
DescriptionSeverityWeakness
Data Sourced
via NVD·10:15 PM
RemedyDescriptionSeverityWeaknessAffected Software
Aug 25, 2021
Advisory Published
via GitHub·02:39 PM

Frequently Asked Questions

1

What is the severity of CVE-2021-37688?

CVE-2021-37688 has been classified as a denial-of-service vulnerability due to the potential for a crash.

2

How do I fix CVE-2021-37688?

To resolve CVE-2021-37688, upgrade TensorFlow to version 2.5.1 or later.

3

Which versions of TensorFlow are affected by CVE-2021-37688?

CVE-2021-37688 affects TensorFlow versions from 2.3.0 to 2.4.3 and the specific 2.5.0 and 2.6.0 release candidates.

4

What kind of attack does CVE-2021-37688 enable?

CVE-2021-37688 can be exploited by an attacker crafting a TFLite model that triggers a null pointer dereference.

5

Is CVE-2021-37688 easy to exploit?

Exploiting CVE-2021-37688 does not typically require advanced skills, making it a concerning vulnerability for users.

Contact

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