CVE-2021-29590
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.
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
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 Low
CVSS: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 Low
CVSS: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 Low
CVSS: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 Low
CVSS: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 Low
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L - CVSS 3.1
- 7.1 High
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H - CVSS 2.0
- 3.6 Low
AV: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 High
CVSS: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 Low
CVSS: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 Low
CVSS: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
| Package | Affected | Fixed |
|---|---|---|
tensorflowPyPI |
before 2.1.4 | 2.1.4 |
tensorflowPyPI |
2.2.0 up to 2.2.3 | 2.2.3 |
tensorflowPyPI |
2.3.0 up to 2.3.3 | 2.3.3 |
tensorflowPyPI |
2.4.0 up to 2.4.2 | 2.4.2 |
tensorflow-cpuPyPI |
before 2.1.4 | 2.1.4 |
tensorflow-cpuPyPI |
2.2.0 up to 2.2.3 | 2.2.3 |
tensorflow-cpuPyPI |
2.3.0 up to 2.3.3 | 2.3.3 |
tensorflow-cpuPyPI |
2.4.0 up to 2.4.2 | 2.4.2 |
tensorflow-gpuPyPI |
before 2.1.4 | 2.1.4 |
tensorflow-gpuPyPI |
2.2.0 up to 2.2.3 | 2.2.3 |
Show 18 moreShow less
| Package | Affected | Fixed |
|---|---|---|
tensorflow-gpuPyPI |
2.3.0 up to 2.3.3 | 2.3.3 |
tensorflow-gpuPyPI |
2.4.0 up to 2.4.2 | 2.4.2 |
tensorflowBitnami |
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 |
tensorflowPyPI |
before 2.1.4, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 35 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.3 |
2.1.4 |
tensorflowPyPI |
2.2.0 up to 2.2.3, plus listed versions 2.2.12.2.2 |
2.2.3 |
tensorflowPyPI |
2.3.0 up to 2.3.3, plus listed versions 2.3.12.3.2 |
2.3.3 |
tensorflowPyPI |
2.4.0 up to 2.4.2, plus listed versions 2.4.1 |
2.4.2 |
tensorflow-cpuPyPI |
before 2.1.4, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 |
2.1.4 |
tensorflow-cpuPyPI |
2.2.0 up to 2.2.3, plus listed versions 2.2.12.2.2 |
2.2.3 |
tensorflow-cpuPyPI |
2.3.0 up to 2.3.3, plus listed versions 2.3.12.3.2 |
2.3.3 |
tensorflow-cpuPyPI |
2.4.0 up to 2.4.2, plus listed versions 2.4.1 |
2.4.2 |
tensorflow-gpuPyPI |
before 2.1.4, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 35 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.3 |
2.1.4 |
tensorflow-gpuPyPI |
2.2.0 up to 2.2.3, plus listed versions 2.2.12.2.2 |
2.2.3 |
tensorflow-gpuPyPI |
2.3.0 up to 2.3.3, plus listed versions 2.3.12.3.2 |
2.3.3 |
tensorflow-gpuPyPI |
2.4.0 up to 2.4.2, plus listed versions 2.4.1 |
2.4.2 |
tensorflowPyPI |
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 less1.0.11.1.01.1.0rc01.1.0rc11.1.0rc21.10.01.10.0rc01.10.0rc11.10.11.11.01.11.0rc01.11.0rc11.11.0rc21.12.01.12.0rc01.12.0rc11.12.0rc21.12.21.12.31.13.0rc01.13.0rc11.13.0rc21.13.11.13.21.14.01.14.0rc01.14.0rc11.15.01.15.0rc01.15.0rc11.15.0rc21.15.0rc31.15.21.15.31.15.41.15.51.2.01.2.0rc01.2.0rc11.2.0rc21.2.11.3.01.3.0rc01.3.0rc11.3.0rc2 |
2.1.42.2.32.3.32.4.2 |
tensorflow-cpuPyPI |
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 less2.2.12.2.22.3.12.3.22.4.1 |
2.1.42.2.32.3.32.4.2 |
tensorflow-gpuPyPI |
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 less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.2.12.2.22.3.12.3.22.4.1 |
2.1.42.2.32.3.32.4.2 |
History
| Recorded | Changed | Sources |
|---|---|---|
| aliases | EUVD | |
| first indexed | CVE 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
github.com/tensorflow/tensorflow/security/advisories/GHSA-24x6-8c7m-hv3f
github.com/tensorflow/tensorflow/commit/953f28dca13c92839ba389c055587cfe6c723578
nvd.nist.gov/vuln/detail/CVE-2021-29590
github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-518.yaml
github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-716.yaml
github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h
github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-227.yaml
github.com/advisories/GHSA-24x6-8c7m-hv3f
github.com/tensorflow/tensorflow
Left out here: 45 versions. The JSON record has them.