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CVE-2021-29590

Heap OOB read in TFLite's implementation of `Minimum` or `Maximum`

2.5 LowFix available

TensorFlow is an end-to-end open source platform for machine learning. The implementations of the Minimum and Maximum TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Attack profile

How easy it is to exploit

Attack vector
Local
Complexity
High
Privileges needed
Low
User interaction
None

What an attacker can affect

Confidentiality
None
Integrity
None
Availability
Low

Exploit likelihood

0.20%Down 0.4 points since May 15, 2021
90%50%10%1%

What each source reports

CVE List Score used 2.5

Heap OOB read in TFLite's implementation of `Minimum` or `Maximum`

TensorFlow is an end-to-end open source platform for machine learning. The implementations of the Minimum and Maximum TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Record
CVE-2021-29590
CVSS 3.1
2.5 LowCVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
Weakness
CWE-125
Updated
2026-11-02
EUVDEUVD-2021-0331 2.5

TensorFlow is an end-to-end open source platform for machine learning. The implementations of the Minimum and Maximum TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Record
EUVD-2021-0331
CVSS 3.1
2.5 LowCVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
Updated
2026-11-03
GitHub AdvisoriesGHSA-24x6-8c7m-hv3f 2.0

Heap OOB read in TFLite's implementation of `Minimum` or `Maximum`

Impact

The implementations of the Minimum and Maximum TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty.

This is because the broadcasting implementation indexes in both tensors with the same index but does not validate that the index is within bounds:

auto maxmin_func = [&](int indexes[N]) {
  output_data[SubscriptToIndex(output_desc, indexes)] =
    op(input1_data[SubscriptToIndex(desc1, indexes)],
        input2_data[SubscriptToIndex(desc2, indexes)]);
};

Patches

We have patched the issue in GitHub commit 953f28dca13c92839ba389c055587cfe6c723578.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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-24x6-8c7m-hv3f
CVSS 4.0
2.0 LowCVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
CVSS 3.1
2.5 LowCVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
Weakness
CWE-125
Updated
2026-11-02
NVD 2.5

TensorFlow is an end-to-end open source platform for machine learning. The implementations of the Minimum and Maximum TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Record
CVE-2021-29590
CVSS 3.1
2.5 LowCVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
CVSS 3.1
7.1 HighCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
CVSS 2.0
3.6 LowAV:L/AC:L/Au:N/C:P/I:N/A:P
Weakness
CWE-125
Updated
2026-11-02
OSV 7.1

TensorFlow is an end-to-end open source platform for machine learning. The implementations of the Minimum and Maximum TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Record
CVE-2021-29590
CVSS 3.1
7.1 HighCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
Updated
2026-11-02
OSVGHSA-24x6-8c7m-hv3f 2.0

Heap OOB read in TFLite's implementation of `Minimum` or `Maximum`

Impact

The implementations of the Minimum and Maximum TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty.

This is because the broadcasting implementation indexes in both tensors with the same index but does not validate that the index is within bounds:

auto maxmin_func = [&](int indexes[N]) {
  output_data[SubscriptToIndex(output_desc, indexes)] =
    op(input1_data[SubscriptToIndex(desc1, indexes)],
        input2_data[SubscriptToIndex(desc2, indexes)]);
};

Patches

We have patched the issue in GitHub commit 953f28dca13c92839ba389c055587cfe6c723578.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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-24x6-8c7m-hv3f
CVSS 4.0
2.0 LowCVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
CVSS 3.1
2.5 LowCVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
Weakness
CWE-125
Updated
2026-11-02
Show 4 moreShow less
OSVBIT-tensorflow-2021-29590 No score

Heap OOB read in TFLite's implementation of `Minimum` or `Maximum`

TensorFlow is an end-to-end open source platform for machine learning. The implementations of the Minimum and Maximum TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Record
BIT-tensorflow-2021-29590
Updated
2026-11-02
OSVPYSEC-2021-227 No score

TensorFlow is an end-to-end open source platform for machine learning. The implementations of the Minimum and Maximum TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Record
PYSEC-2021-227
Updated
2026-11-02
OSVPYSEC-2021-518 No score

TensorFlow is an end-to-end open source platform for machine learning. The implementations of the Minimum and Maximum TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Record
PYSEC-2021-518
Updated
2026-11-02
OSVPYSEC-2021-716 No score

TensorFlow is an end-to-end open source platform for machine learning. The implementations of the Minimum and Maximum TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Record
PYSEC-2021-716
Updated
2026-11-02

Affected products

Affected packages

Affected packages
PackageAffectedFixed
tensorflow
PyPI
before 2.1.4
2.1.4
tensorflow
PyPI
2.2.0 up to 2.2.3
2.2.3
tensorflow
PyPI
2.3.0 up to 2.3.3
2.3.3
tensorflow
PyPI
2.4.0 up to 2.4.2
2.4.2
tensorflow-cpu
PyPI
before 2.1.4
2.1.4
tensorflow-cpu
PyPI
2.2.0 up to 2.2.3
2.2.3
tensorflow-cpu
PyPI
2.3.0 up to 2.3.3
2.3.3
tensorflow-cpu
PyPI
2.4.0 up to 2.4.2
2.4.2
tensorflow-gpu
PyPI
before 2.1.4
2.1.4
tensorflow-gpu
PyPI
2.2.0 up to 2.2.3
2.2.3
Show 18 moreShow less
Affected packages
PackageAffectedFixed
tensorflow-gpu
PyPI
2.3.0 up to 2.3.3
2.3.3
tensorflow-gpu
PyPI
2.4.0 up to 2.4.2
2.4.2
tensorflow
Bitnami
before 2.1.4, 2.2.0 up to 2.2.3, 2.3.0 up to 2.3.3, 2.4.0 up to 2.4.2
2.1.42.2.32.3.32.4.2
tensorflow
PyPI
before 2.1.4, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 35 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.3
2.1.4
tensorflow
PyPI
2.2.0 up to 2.2.3, plus listed versions
2.2.12.2.2
2.2.3
tensorflow
PyPI
2.3.0 up to 2.3.3, plus listed versions
2.3.12.3.2
2.3.3
tensorflow
PyPI
2.4.0 up to 2.4.2, plus listed versions
2.4.1
2.4.2
tensorflow-cpu
PyPI
before 2.1.4, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
2.1.4
tensorflow-cpu
PyPI
2.2.0 up to 2.2.3, plus listed versions
2.2.12.2.2
2.2.3
tensorflow-cpu
PyPI
2.3.0 up to 2.3.3, plus listed versions
2.3.12.3.2
2.3.3
tensorflow-cpu
PyPI
2.4.0 up to 2.4.2, plus listed versions
2.4.1
2.4.2
tensorflow-gpu
PyPI
before 2.1.4, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 35 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.3
2.1.4
tensorflow-gpu
PyPI
2.2.0 up to 2.2.3, plus listed versions
2.2.12.2.2
2.2.3
tensorflow-gpu
PyPI
2.3.0 up to 2.3.3, plus listed versions
2.3.12.3.2
2.3.3
tensorflow-gpu
PyPI
2.4.0 up to 2.4.2, plus listed versions
2.4.1
2.4.2
tensorflow
PyPI
before 2.1.4, 2.2.0 up to 2.2.3, 2.3.0 up to 2.3.3, 2.4.0 up to 2.4.2, plus listed versions
0.12.00.12.0rc00.12.0rc10.12.11.0.0
Show 45 moreShow less
1.0.11.1.01.1.0rc01.1.0rc11.1.0rc21.10.01.10.0rc01.10.0rc11.10.11.11.01.11.0rc01.11.0rc11.11.0rc21.12.01.12.0rc01.12.0rc11.12.0rc21.12.21.12.31.13.0rc01.13.0rc11.13.0rc21.13.11.13.21.14.01.14.0rc01.14.0rc11.15.01.15.0rc01.15.0rc11.15.0rc21.15.0rc31.15.21.15.31.15.41.15.51.2.01.2.0rc01.2.0rc11.2.0rc21.2.11.3.01.3.0rc01.3.0rc11.3.0rc2
2.1.42.2.32.3.32.4.2
tensorflow-cpu
PyPI
before 2.1.4, 2.2.0 up to 2.2.3, 2.3.0 up to 2.3.3, 2.4.0 up to 2.4.2, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 5 moreShow less
2.2.12.2.22.3.12.3.22.4.1
2.1.42.2.32.3.32.4.2
tensorflow-gpu
PyPI
before 2.1.4, 2.2.0 up to 2.2.3, 2.3.0 up to 2.3.3, 2.4.0 up to 2.4.2, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 40 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.2.12.2.22.3.12.3.22.4.1
2.1.42.2.32.3.32.4.2

History

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

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

In short

CVE-2021-29590 is a low vulnerability (CVSS 2.5) in Google Tensorflow, published May 14, 2021. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.20%, the 9th percentile. Fixed in tensorflow 2.1.4.

References

This page doesn't list everything

Left out here: 45 versions. The JSON record has them.

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