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CVE-2021-37644

`std::abort` raised from `TensorListReserve` in TensorFlow

5.5 MediumFix available

TensorFlow is an end-to-end open source platform for machine learning. In affected versions providing a negative element to num_elements list argument of tf.raw_ops.TensorListReserve causes the runtime to abort the process due to reallocating a std::vector to have a negative number of elements. The implementation calls std::vector.resize() with the new size controlled by input given by the user, without checking that this input is valid. We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2. 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.

Attack profile

How easy it is to exploit

Attack vector
Local
Complexity
Low
Privileges needed
Low
User interaction
None

What an attacker can affect

Confidentiality
None
Integrity
None
Availability
High

Exploit likelihood

0.15%Down 0.5 points since Aug 13, 2021
90%50%10%1%

What each source reports

CVE List Score used 5.5

`std::abort` raised from `TensorListReserve` in TensorFlow

TensorFlow is an end-to-end open source platform for machine learning. In affected versions providing a negative element to num_elements list argument of tf.raw_ops.TensorListReserve causes the runtime to abort the process due to reallocating a std::vector to have a negative number of elements. The implementation calls std::vector.resize() with the new size controlled by input given by the user, without checking that this input is valid. We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2. 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.

Record
CVE-2021-37644
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-617
Updated
2026-11-02
EUVDEUVD-2021-0370 5.5

TensorFlow is an end-to-end open source platform for machine learning. In affected versions providing a negative element to num_elements list argument of tf.raw_ops.TensorListReserve causes the runtime to abort the process due to reallocating a std::vector to have a negative number of elements. The implementation calls std::vector.resize() with the new size controlled by input given by the user, without checking that this input is valid. We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2. 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.

Record
EUVD-2021-0370
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-03
GitHub AdvisoriesGHSA-27j5-4p9v-pp67 5.7

`std::abort` raised from `TensorListReserve`

Impact

Providing a negative element to num_elements list argument of tf.raw_ops.TensorListReserve causes the runtime to abort the process due to reallocating a std::vector to have a negative number of elements:

import tensorflow as tf

tf.raw_ops.TensorListReserve(
  element_shape = tf.constant([1]),
  num_elements=tf.constant([-1]),
  element_dtype = tf.int32)

The implementation calls std::vector.resize() with the new size controlled by input given by the user, without checking that this input is valid.

Patches

We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2.

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.

Record
GHSA-27j5-4p9v-pp67
CVSS 4.0
5.7 MediumCVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-617
Updated
2026-11-02
NVD 5.5

TensorFlow is an end-to-end open source platform for machine learning. In affected versions providing a negative element to num_elements list argument of tf.raw_ops.TensorListReserve causes the runtime to abort the process due to reallocating a std::vector to have a negative number of elements. The implementation calls std::vector.resize() with the new size controlled by input given by the user, without checking that this input is valid. We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2. 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.

Record
CVE-2021-37644
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVSS 2.0
2.1 LowAV:L/AC:L/Au:N/C:N/I:N/A:P
Weakness
CWE-617
Updated
2026-11-02
OSV 5.5

TensorFlow is an end-to-end open source platform for machine learning. In affected versions providing a negative element to num_elements list argument of tf.raw_ops.TensorListReserve causes the runtime to abort the process due to reallocating a std::vector to have a negative number of elements. The implementation calls std::vector.resize() with the new size controlled by input given by the user, without checking that this input is valid. We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2. 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.

Record
CVE-2021-37644
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
OSVGHSA-27j5-4p9v-pp67 5.7

`std::abort` raised from `TensorListReserve`

Impact

Providing a negative element to num_elements list argument of tf.raw_ops.TensorListReserve causes the runtime to abort the process due to reallocating a std::vector to have a negative number of elements:

import tensorflow as tf

tf.raw_ops.TensorListReserve(
  element_shape = tf.constant([1]),
  num_elements=tf.constant([-1]),
  element_dtype = tf.int32)

The implementation calls std::vector.resize() with the new size controlled by input given by the user, without checking that this input is valid.

Patches

We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2.

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.

Record
GHSA-27j5-4p9v-pp67
CVSS 4.0
5.7 MediumCVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-617
Updated
2026-11-02
Show 6 moreShow less
OSVBIT-tensorflow-2021-37644 No score

`std::abort` raised from `TensorListReserve` in TensorFlow

TensorFlow is an end-to-end open source platform for machine learning. In affected versions providing a negative element to num_elements list argument of tf.raw_ops.TensorListReserve causes the runtime to abort the process due to reallocating a std::vector to have a negative number of elements. The implementation calls std::vector.resize() with the new size controlled by input given by the user, without checking that this input is valid. We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2. 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.

Record
BIT-tensorflow-2021-37644
Updated
2026-11-02
OSVopenSUSE-SU-2022:10014-1 No score

Security update for tensorflow2

This update for tensorflow fixes the following issues:

Update to TF2 2.6.0 which fixes multiple CVEs (boo#1189423).

  • Introduction of bazel6.3 and basel-skylib1.0.3 as build dependencies. The latter has been adapted to all a version in its package name (if %set_ver_suffix is set to 1). This allows multiple versions to exist for one product (not installed). NOTE: basel-skylib1.0.3 does not exist in oS:Factory: basel-skylib in oS:Factory - the base version - is 1.0.3.
Record
openSUSE-SU-2022:10014-1
Updated
2026-11-02
OSVopenSUSE-SU-2024:12116-1 No score

tensorflow-lite-2.9.1-1.1 on GA media

These are all security issues fixed in the tensorflow-lite-2.9.1-1.1 package on the GA media of openSUSE Tumbleweed.

Record
openSUSE-SU-2024:12116-1
Updated
2026-11-02
OSVPYSEC-2021-266 No score

TensorFlow is an end-to-end open source platform for machine learning. In affected versions providing a negative element to num_elements list argument of tf.raw_ops.TensorListReserve causes the runtime to abort the process due to reallocating a std::vector to have a negative number of elements. The implementation calls std::vector.resize() with the new size controlled by input given by the user, without checking that this input is valid. We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2. 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.

Record
PYSEC-2021-266
Updated
2026-11-02
OSVPYSEC-2021-557 No score

TensorFlow is an end-to-end open source platform for machine learning. In affected versions providing a negative element to num_elements list argument of tf.raw_ops.TensorListReserve causes the runtime to abort the process due to reallocating a std::vector to have a negative number of elements. The implementation calls std::vector.resize() with the new size controlled by input given by the user, without checking that this input is valid. We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2. 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.

Record
PYSEC-2021-557
Updated
2026-11-02
OSVPYSEC-2021-755 No score

TensorFlow is an end-to-end open source platform for machine learning. In affected versions providing a negative element to num_elements list argument of tf.raw_ops.TensorListReserve causes the runtime to abort the process due to reallocating a std::vector to have a negative number of elements. The implementation calls std::vector.resize() with the new size controlled by input given by the user, without checking that this input is valid. We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2. 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.

Record
PYSEC-2021-755
Updated
2026-11-02

Affected products

Affected packages

Affected packages
PackageAffectedFixed
tensorflow
PyPI
 before 2.3.4
2.3.4
tensorflow
PyPI
 2.4.0 up to 2.4.3
2.4.3
tensorflow
PyPI
 2.5.0 to 2.5.0
2.5.1
tensorflow-cpu
PyPI
 before 2.3.4
2.3.4
tensorflow-cpu
PyPI
 2.4.0 up to 2.4.3
2.4.3
tensorflow-cpu
PyPI
 2.5.0 to 2.5.0
2.5.1
tensorflow-gpu
PyPI
 before 2.3.4
2.3.4
tensorflow-gpu
PyPI
 2.4.0 up to 2.4.3
2.4.3
tensorflow-gpu
PyPI
 2.5.0 to 2.5.0
2.5.1
tensorflow
Bitnami
 2.3.0 up to 2.3.4, 2.4.0 up to 2.4.3, 2.5.0 up to 2.5.1
2.3.42.4.32.5.1
Show 24 moreShow less
Affected packages
PackageAffectedFixed
tensorflow
PyPI
 before 2.3.4, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 44 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.3
2.3.4
tensorflow
PyPI
 2.4.0 up to 2.4.3, plus listed versions
2.4.12.4.2
2.4.3
tensorflow
PyPI
 2.5.0 up to 2.5.1
2.5.1
tensorflow-cpu
PyPI
 before 2.3.4, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 9 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.3
2.3.4
tensorflow-cpu
PyPI
 2.4.0 up to 2.4.3, plus listed versions
2.4.12.4.2
2.4.3
tensorflow-cpu
PyPI
 2.5.0 up to 2.5.1
2.5.1
tensorflow-gpu
PyPI
 before 2.3.4, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 44 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.3
2.3.4
tensorflow-gpu
PyPI
 2.4.0 up to 2.4.3, plus listed versions
2.4.12.4.2
2.4.3
tensorflow-gpu
PyPI
 2.5.0 up to 2.5.1
2.5.1
tensorflow
PyPI
 2.3.0 up to 2.3.4, 2.4.0 up to 2.4.3, plus listed versions
2.3.12.3.22.3.32.4.12.4.2
2.3.42.4.3
tensorflow-cpu
PyPI
 2.3.0 up to 2.3.4, 2.4.0 up to 2.4.3, plus listed versions
2.3.12.3.22.3.32.4.12.4.2
2.3.42.4.3
tensorflow-gpu
PyPI
 2.3.0 up to 2.3.4, 2.4.0 up to 2.4.3, plus listed versions
2.3.12.3.22.3.32.4.12.4.2
2.3.42.4.3
bazel-skylib1.0.3
SUSE:Package Hub 15 SP3
From an advisory covering 63 CVEs
 before 1.0.3-bp153.2.1
1.0.3-bp153.2.1
bazel3.7
SUSE:Package Hub 15 SP3
From an advisory covering 63 CVEs
 before 3.7.2-bp153.4.1
3.7.2-bp153.4.1
tensorflow2
SUSE:Package Hub 15 SP3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1
tensorflow2-lite
SUSE:Package Hub 15 SP3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1
tensorflow2_2_6_0-gnu-hpc
SUSE:Package Hub 15 SP3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1
tensorflow2_2_6_0-gnu-openmpi2-hpc
SUSE:Package Hub 15 SP3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1
bazel-skylib1.0.3
openSUSE:Leap 15.3
From an advisory covering 63 CVEs
 before 1.0.3-bp153.2.1
1.0.3-bp153.2.1
bazel3.7
openSUSE:Leap 15.3
From an advisory covering 63 CVEs
 before 3.7.2-bp153.4.1
3.7.2-bp153.4.1
tensorflow2
openSUSE:Leap 15.3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1
tensorflow2-lite
openSUSE:Leap 15.3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1
tensorflow2_2_6_0-gnu-hpc
openSUSE:Leap 15.3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1
tensorflow2_2_6_0-gnu-openmpi2-hpc
openSUSE:Leap 15.3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1

History

History
RecordedChangedSources
affected, facts
aliasesEUVD
first indexedCVE List, GitHub Advisories, NVD, OSV

Dates are when Every CVE recorded each change. Upstream dates may differ.

In short

CVE-2021-37644 is a medium vulnerability (CVSS 5.5) in Google Tensorflow, published August 12, 2021. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.15%, the 4th percentile. Fixed in tensorflow 2.3.4.

References

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