CVE-2022-29200
Missing validation causes denial of service in TensorFlow via `LSTMBlockCell`
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.raw_ops.LSTMBlockCell does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack. The code does not validate the ranks of any of the arguments to this API call. This results in CHECK-failures when the elements of the tensor are accessed. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
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
What each source reports
CVE List Score used
5.5
Missing validation causes denial of service in TensorFlow via `LSTMBlockCell`
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.raw_ops.LSTMBlockCell does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack. The code does not validate the ranks of any of the arguments to this API call. This results in CHECK-failures when the elements of the tensor are accessed. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
- Record
CVE-2022-29200- CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - Weakness
- CWE-20
- Updated
- 2026-11-02
EUVDEUVD-2022-2054
5.5
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.raw_ops.LSTMBlockCell does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack. The code does not validate the ranks of any of the arguments to this API call. This results in CHECK-failures when the elements of the tensor are accessed. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
- Record
EUVD-2022-2054- CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - Updated
- 2026-11-02
GitHub AdvisoriesGHSA-2vv3-56qg-g2cf
5.5
Missing validation causes denial of service via `LSTMBlockCell`
Impact
The implementation of tf.raw_ops.LSTMBlockCell does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:
import tensorflow as tf
tf.raw_ops.LSTMBlockCell(
x=tf.constant(0.837607, shape=[28,29], dtype=tf.float32),
cs_prev=tf.constant(0, shape=[28,17], dtype=tf.float32),
h_prev=tf.constant(0.592631638, shape=[28,17], dtype=tf.float32),
w=tf.constant(0.887386262, shape=[46,68], dtype=tf.float32),
wci=tf.constant(0, shape=[], dtype=tf.float32),
wcf=tf.constant(0, shape=[17], dtype=tf.float32),
wco=tf.constant(0.592631638, shape=[28,17], dtype=tf.float32),
b=tf.constant(0.75259006, shape=[68], dtype=tf.float32),
forget_bias=1, cell_clip=0, use_peephole=False)
The code does not validate the ranks of any of the arguments to this API call. This results in CHECK-failures when the elements of the tensor are accessed.
Patches
We have patched the issue in GitHub commit 803404044ae7a1efac48ba82d74111fce1ddb09a.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.
- Record
GHSA-2vv3-56qg-g2cf- CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - Weakness
- CWE-20, CWE-1284
- Updated
- 2026-11-02
NVD
5.5
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.raw_ops.LSTMBlockCell does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack. The code does not validate the ranks of any of the arguments to this API call. This results in CHECK-failures when the elements of the tensor are accessed. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
- Record
CVE-2022-29200- CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - CVSS 2.0
- 2.1 Low
AV:L/AC:L/Au:N/C:N/I:N/A:P - Weakness
- CWE-20, CWE-1284
- Updated
- 2026-11-02
OSV
5.5
Missing validation causes denial of service in TensorFlow via `LSTMBlockCell`
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.raw_ops.LSTMBlockCell does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack. The code does not validate the ranks of any of the arguments to this API call. This results in CHECK-failures when the elements of the tensor are accessed. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
- Record
CVE-2022-29200- CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - Weakness
- CWE-20
- Updated
- 2026-11-02
OSVGHSA-2vv3-56qg-g2cf
5.5
Missing validation causes denial of service via `LSTMBlockCell`
Impact
The implementation of tf.raw_ops.LSTMBlockCell does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:
import tensorflow as tf
tf.raw_ops.LSTMBlockCell(
x=tf.constant(0.837607, shape=[28,29], dtype=tf.float32),
cs_prev=tf.constant(0, shape=[28,17], dtype=tf.float32),
h_prev=tf.constant(0.592631638, shape=[28,17], dtype=tf.float32),
w=tf.constant(0.887386262, shape=[46,68], dtype=tf.float32),
wci=tf.constant(0, shape=[], dtype=tf.float32),
wcf=tf.constant(0, shape=[17], dtype=tf.float32),
wco=tf.constant(0.592631638, shape=[28,17], dtype=tf.float32),
b=tf.constant(0.75259006, shape=[68], dtype=tf.float32),
forget_bias=1, cell_clip=0, use_peephole=False)
The code does not validate the ranks of any of the arguments to this API call. This results in CHECK-failures when the elements of the tensor are accessed.
Patches
We have patched the issue in GitHub commit 803404044ae7a1efac48ba82d74111fce1ddb09a.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.
- Record
GHSA-2vv3-56qg-g2cf- CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - Weakness
- CWE-1284, CWE-20
- Updated
- 2026-11-02
Show 4 moreShow less
OSVPYSEC-2026-3089
5.5
Missing validation causes denial of service via `LSTMBlockCell`
Impact
The implementation of tf.raw_ops.LSTMBlockCell does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:
import tensorflow as tf
tf.raw_ops.LSTMBlockCell(
x=tf.constant(0.837607, shape=[28,29], dtype=tf.float32),
cs_prev=tf.constant(0, shape=[28,17], dtype=tf.float32),
h_prev=tf.constant(0.592631638, shape=[28,17], dtype=tf.float32),
w=tf.constant(0.887386262, shape=[46,68], dtype=tf.float32),
wci=tf.constant(0, shape=[], dtype=tf.float32),
wcf=tf.constant(0, shape=[17], dtype=tf.float32),
wco=tf.constant(0.592631638, shape=[28,17], dtype=tf.float32),
b=tf.constant(0.75259006, shape=[68], dtype=tf.float32),
forget_bias=1, cell_clip=0, use_peephole=False)
The code does not validate the ranks of any of the arguments to this API call. This results in CHECK-failures when the elements of the tensor are accessed.
Patches
We have patched the issue in GitHub commit 803404044ae7a1efac48ba82d74111fce1ddb09a.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.
- Record
PYSEC-2026-3089- CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - Updated
- 2026-11-02
OSVPYSEC-2026-3267
5.5
Missing validation causes denial of service via `LSTMBlockCell`
Impact
The implementation of tf.raw_ops.LSTMBlockCell does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:
import tensorflow as tf
tf.raw_ops.LSTMBlockCell(
x=tf.constant(0.837607, shape=[28,29], dtype=tf.float32),
cs_prev=tf.constant(0, shape=[28,17], dtype=tf.float32),
h_prev=tf.constant(0.592631638, shape=[28,17], dtype=tf.float32),
w=tf.constant(0.887386262, shape=[46,68], dtype=tf.float32),
wci=tf.constant(0, shape=[], dtype=tf.float32),
wcf=tf.constant(0, shape=[17], dtype=tf.float32),
wco=tf.constant(0.592631638, shape=[28,17], dtype=tf.float32),
b=tf.constant(0.75259006, shape=[68], dtype=tf.float32),
forget_bias=1, cell_clip=0, use_peephole=False)
The code does not validate the ranks of any of the arguments to this API call. This results in CHECK-failures when the elements of the tensor are accessed.
Patches
We have patched the issue in GitHub commit 803404044ae7a1efac48ba82d74111fce1ddb09a.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.
- Record
PYSEC-2026-3267- CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - Updated
- 2026-11-02
OSVPYSEC-2026-944
5.5
Missing validation causes denial of service via `LSTMBlockCell`
Impact
The implementation of tf.raw_ops.LSTMBlockCell does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:
import tensorflow as tf
tf.raw_ops.LSTMBlockCell(
x=tf.constant(0.837607, shape=[28,29], dtype=tf.float32),
cs_prev=tf.constant(0, shape=[28,17], dtype=tf.float32),
h_prev=tf.constant(0.592631638, shape=[28,17], dtype=tf.float32),
w=tf.constant(0.887386262, shape=[46,68], dtype=tf.float32),
wci=tf.constant(0, shape=[], dtype=tf.float32),
wcf=tf.constant(0, shape=[17], dtype=tf.float32),
wco=tf.constant(0.592631638, shape=[28,17], dtype=tf.float32),
b=tf.constant(0.75259006, shape=[68], dtype=tf.float32),
forget_bias=1, cell_clip=0, use_peephole=False)
The code does not validate the ranks of any of the arguments to this API call. This results in CHECK-failures when the elements of the tensor are accessed.
Patches
We have patched the issue in GitHub commit 803404044ae7a1efac48ba82d74111fce1ddb09a.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.
- Record
PYSEC-2026-944- CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - Updated
- 2026-11-02
OSVBIT-tensorflow-2022-29200 No score
Missing validation causes denial of service in TensorFlow via `LSTMBlockCell`
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.raw_ops.LSTMBlockCell does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack. The code does not validate the ranks of any of the arguments to this API call. This results in CHECK-failures when the elements of the tensor are accessed. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
- Record
BIT-tensorflow-2022-29200- Updated
- 2026-11-02
Affected products
Affected packages
| Package | Affected | Fixed |
|---|---|---|
tensorflowPyPI |
before 2.6.4 | 2.6.4 |
tensorflowPyPI |
2.7.0 up to 2.7.2 | 2.7.2 |
tensorflowPyPI |
2.8.0 up to 2.8.1 | 2.8.1 |
tensorflow-cpuPyPI |
before 2.6.4 | 2.6.4 |
tensorflow-cpuPyPI |
2.7.0 up to 2.7.2 | 2.7.2 |
tensorflow-cpuPyPI |
2.8.0 up to 2.8.1 | 2.8.1 |
tensorflow-gpuPyPI |
before 2.6.4 | 2.6.4 |
tensorflow-gpuPyPI |
2.7.0 up to 2.7.2 | 2.7.2 |
tensorflow-gpuPyPI |
2.8.0 up to 2.8.1 | 2.8.1 |
tensorflowBitnami |
before 2.6.4, 2.7.0 up to 2.7.2, 2.8.0 up to 2.8.1 | 2.6.42.7.22.8.1 |
Show 9 moreShow less
| Package | Affected | Fixed |
|---|---|---|
tensorflowPyPI |
before 2.6.4, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 45 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4 |
2.6.4 |
tensorflowPyPI |
2.7.0 up to 2.7.2, plus listed versions 2.7.1 |
2.7.2 |
tensorflow-cpuPyPI |
before 2.6.4, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 Show 23 moreShow less2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.3 |
2.6.4 |
tensorflow-cpuPyPI |
2.7.0 up to 2.7.2, plus listed versions 2.7.1 |
2.7.2 |
tensorflow-gpuPyPI |
before 2.6.4, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 45 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4 |
2.6.4 |
tensorflow-gpuPyPI |
2.7.0 up to 2.7.2, plus listed versions 2.7.1 |
2.7.2 |
tensorflowPyPI |
before 2.6.4, 2.7.0 up to 2.7.2, 2.8.0 up to 2.8.1, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 45 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4 |
2.6.42.7.22.8.1 |
tensorflow-cpuPyPI |
before 2.6.4, 2.7.0 up to 2.7.2, 2.8.0 up to 2.8.1, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 Show 24 moreShow less2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.7.1 |
2.6.42.7.22.8.1 |
tensorflow-gpuPyPI |
before 2.6.4, 2.7.0 up to 2.7.2, 2.8.0 up to 2.8.1, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 45 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4 |
2.6.42.7.22.8.1 |
History
| Recorded | Changed | Sources |
|---|---|---|
| first indexed | CVE List, EUVD, GitHub Advisories, NVD, OSV |
Dates are when Every CVE recorded each change. Upstream dates may differ.
In short
CVE-2022-29200 is a medium vulnerability (CVSS 5.5) in Google Tensorflow, published May 20, 2022. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.33%, the 25th percentile. Fixed in tensorflow 2.6.4.
References
github.com/tensorflow/tensorflow/releases/tag/v2.6.4
github.com/tensorflow/tensorflow/releases/tag/v2.7.2
github.com/tensorflow/tensorflow/releases/tag/v2.8.1
github.com/tensorflow/tensorflow/releases/tag/v2.9.0
github.com/tensorflow/tensorflow/security/advisories/GHSA-2vv3-56qg-g2cf
github.com/tensorflow/tensorflow/commit/803404044ae7a1efac48ba82d74111fce1ddb09a
Show 8 moreShow less
github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/rnn/lstm_ops.cc
nvd.nist.gov/vuln/detail/CVE-2022-29200
github.com/advisories/GHSA-2vv3-56qg-g2cf
github.com/CVEProject/cvelistV5/tree/main/cves/2022/29xxx/CVE-2022-29200.json
github.com/tensorflow/tensorflow
pypi.org/project/tensorflow
pypi.org/project/tensorflow-cpu
pypi.org/project/tensorflow-gpu
Left out here: 60 versions. The JSON record has them.