CVE-2020-15198
Heap buffer overflow in Tensorflow
In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Attack profile
How easy it is to exploit
- Attack vector
- Network
- Complexity
- High
- Privileges needed
- None
- User interaction
- None
What an attacker can affect
- Confidentiality
- Low
- Integrity
- Low
- Availability
- None
Exploit likelihood
What each source reports
CVE List Score used
Heap buffer overflow in Tensorflow
In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
- Record
CVE-2020-15198- CVSS 3.1
- 5.4 Medium
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N - Weakness
- CWE-122, CWE-119
- Updated
- 2026-11-02
EUVDEUVD-2020-0194
In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
- Record
EUVD-2020-0194- CVSS 3.1
- 5.4 Medium
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N - Updated
- 2026-11-03
GitHub AdvisoriesGHSA-jc87-6vpp-7ff3
Heap buffer overflow in Tensorflow
Impact
The SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L193-L195
Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers.
Patches
We have patched the issue in 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and will release a patch release.
We recommend users to upgrade to TensorFlow 2.3.1.
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 is a variant of GHSA-p5f8-gfw5-33w4
- Record
GHSA-jc87-6vpp-7ff3- CVSS 4.0
- 6.3 Medium
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:N/SC:L/SI:L/SA:N - CVSS 3.1
- 5.4 Medium
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N - Weakness
- CWE-119, CWE-122
- Updated
- 2026-11-02
NVD
In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
- Record
CVE-2020-15198- CVSS 3.1
- 5.4 Medium
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N - CVSS 2.0
- 5.8 Medium
AV:N/AC:M/Au:N/C:P/I:P/A:N - Weakness
- CWE-119, CWE-122
- Updated
- 2026-11-02
OSV
In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
- Record
CVE-2020-15198- CVSS 3.1
- 5.4 Medium
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N - Updated
- 2026-11-02
OSVGHSA-jc87-6vpp-7ff3
Heap buffer overflow in Tensorflow
Impact
The SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L193-L195
Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers.
Patches
We have patched the issue in 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and will release a patch release.
We recommend users to upgrade to TensorFlow 2.3.1.
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 is a variant of GHSA-p5f8-gfw5-33w4
- Record
GHSA-jc87-6vpp-7ff3- CVSS 4.0
- 6.3 Medium
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:N/SC:L/SI:L/SA:N - CVSS 3.1
- 5.4 Medium
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N - Weakness
- CWE-119, CWE-122
- Updated
- 2026-11-02
Show 4 moreShow less
OSVBIT-tensorflow-2020-15198 No score
Heap buffer overflow in Tensorflow
In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
- Record
BIT-tensorflow-2020-15198- Updated
- 2026-11-02
OSVPYSEC-2020-121 No score
In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
- Record
PYSEC-2020-121- Updated
- 2026-11-02
OSVPYSEC-2020-278 No score
In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
- Record
PYSEC-2020-278- Updated
- 2026-11-02
OSVPYSEC-2020-313 No score
In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
- Record
PYSEC-2020-313- Updated
- 2026-11-02
Affected products
Affected packages
| Package | Affected | Fixed |
|---|---|---|
tensorflowPyPI |
2.3.0 to 2.3.0 | 2.3.1 |
tensorflow-cpuPyPI |
2.3.0 to 2.3.0 | 2.3.1 |
tensorflow-gpuPyPI |
2.3.0 to 2.3.0 | 2.3.1 |
tensorflowBitnami |
2.3.0 up to 2.3.1 | 2.3.1 |
tensorflowPyPI |
2.3.0 up to 2.3.1 | 2.3.1 |
tensorflow-cpuPyPI |
2.3.0 up to 2.3.1 | 2.3.1 |
tensorflow-gpuPyPI |
2.3.0 up to 2.3.1 | 2.3.1 |
tensorflowPyPI |
before 2.3.1, plus listed versions 0.12.0rc00.12.0rc10.12.00.12.11.0.0 Show 45 moreShow less1.0.11.1.0rc01.1.0rc11.1.0rc21.1.01.2.0rc01.2.0rc11.2.0rc21.2.01.2.11.3.0rc01.3.0rc11.3.0rc21.3.01.4.0rc01.4.0rc11.4.01.4.11.5.0rc01.5.0rc11.5.01.5.11.6.0rc01.6.0rc11.6.01.7.0rc01.7.0rc11.7.01.7.11.8.0rc01.8.0rc11.8.01.9.0rc01.9.0rc11.9.0rc21.9.01.10.0rc01.10.0rc11.10.01.10.11.11.0rc01.11.0rc11.11.0rc21.11.01.12.0rc0 |
2.3.1 |
tensorflow-cpuPyPI |
before 2.3.1, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 Show 6 moreShow less2.1.42.2.02.2.12.2.22.2.32.3.0 |
2.3.1 |
tensorflow-gpuPyPI |
before 2.3.1, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 41 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.0 |
2.3.1 |
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-2020-15198 is a medium vulnerability (CVSS 5.4) in Google Tensorflow, published September 25, 2020. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.54%, the 45th percentile. Fixed in tensorflow 2.3.1.
References
github.com/tensorflow/tensorflow/releases/tag/v2.3.1
nvd.nist.gov/vuln/detail/CVE-2020-15198
Left out here: 54 versions. The JSON record has them.