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CVE-2022-23589

Null pointer dereference in Grappler's `IsConstant` in Tensorflow

6.5 MediumFix available

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a SavedModel file (fixing the first one would trigger the same dereference in the second place). First, during constant folding, the GraphDef might not have the required nodes for the binary operation. If a node is missing, the correposning mul_*child would be null, and the dereference in the subsequent line would be incorrect. We have a similar issue during IsIdentityConsumingSwitch. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Attack profile

How easy it is to exploit

Attack vector
Network
Complexity
Low
Privileges needed
Low
User interaction
None

What an attacker can affect

Confidentiality
None
Integrity
None
Availability
High

Exploit likelihood

1.11%Up 0.2 points since Feb 8, 2022
90%50%10%1%

What each source reports

CVE List Score used 6.5

Null pointer dereference in Grappler's `IsConstant` in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a SavedModel file (fixing the first one would trigger the same dereference in the second place). First, during constant folding, the GraphDef might not have the required nodes for the binary operation. If a node is missing, the correposning mul_*child would be null, and the dereference in the subsequent line would be incorrect. We have a similar issue during IsIdentityConsumingSwitch. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Record
CVE-2022-23589
CVSS 3.1
6.5 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-476
Updated
2026-11-02
EUVDEUVD-2022-0337 6.5

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a SavedModel file (fixing the first one would trigger the same dereference in the second place). First, during constant folding, the GraphDef might not have the required nodes for the binary operation. If a node is missing, the correposning mul_*child would be null, and the dereference in the subsequent line would be incorrect. We have a similar issue during IsIdentityConsumingSwitch. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Record
EUVD-2022-0337
CVSS 3.1
6.5 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
GitHub AdvisoriesGHSA-9px9-73fg-3fqp 6.5

Null pointer dereference in Grappler's `IsConstant`

Impact

Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a SavedModel file (fixing the first one would trigger the same dereference in the second place):

First, during constant folding, the GraphDef might not have the required nodes for the binary operation:

  NodeDef* mul_left_child = node_map_->GetNode(node->input(0));
  NodeDef* mul_right_child = node_map_->GetNode(node->input(1));
  // One child must be constant, and the second must be Conv op.
  const bool left_child_is_constant = IsReallyConstant(*mul_left_child);
  const bool right_child_is_constant = IsReallyConstant(*mul_right_child);

If a node is missing, the correposning mul_*child would be null, and the dereference in the subsequent line would be incorrect.

We have a similar issue during IsIdentityConsumingSwitch:

  NodeDef* input_node = graph.GetNode(tensor_id.node());
  return IsSwitch(*input_node);

Patches

We have patched the issue in GitHub commits 0a365c029e437be0349c31f8d4c9926b69fa3fa1 and 045deec1cbdebb27d817008ad5df94d96a08b1bf.

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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.

Record
GHSA-9px9-73fg-3fqp
CVSS 3.1
6.5 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-476
Updated
2026-11-02
NVD 6.5

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a SavedModel file (fixing the first one would trigger the same dereference in the second place). First, during constant folding, the GraphDef might not have the required nodes for the binary operation. If a node is missing, the correposning mul_*child would be null, and the dereference in the subsequent line would be incorrect. We have a similar issue during IsIdentityConsumingSwitch. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Record
CVE-2022-23589
CVSS 3.1
6.5 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVSS 2.0
4.0 MediumAV:N/AC:L/Au:S/C:N/I:N/A:P
Weakness
CWE-476
Updated
2026-11-02
OSV 6.5

Null pointer dereference in Grappler's `IsConstant` in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a SavedModel file (fixing the first one would trigger the same dereference in the second place). First, during constant folding, the GraphDef might not have the required nodes for the binary operation. If a node is missing, the correposning mul_*child would be null, and the dereference in the subsequent line would be incorrect. We have a similar issue during IsIdentityConsumingSwitch. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Record
CVE-2022-23589
CVSS 3.1
6.5 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-476
Updated
2026-11-02
OSVGHSA-9px9-73fg-3fqp 6.5

Null pointer dereference in Grappler's `IsConstant`

Impact

Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a SavedModel file (fixing the first one would trigger the same dereference in the second place):

First, during constant folding, the GraphDef might not have the required nodes for the binary operation:

  NodeDef* mul_left_child = node_map_->GetNode(node->input(0));
  NodeDef* mul_right_child = node_map_->GetNode(node->input(1));
  // One child must be constant, and the second must be Conv op.
  const bool left_child_is_constant = IsReallyConstant(*mul_left_child);
  const bool right_child_is_constant = IsReallyConstant(*mul_right_child);

If a node is missing, the correposning mul_*child would be null, and the dereference in the subsequent line would be incorrect.

We have a similar issue during IsIdentityConsumingSwitch:

  NodeDef* input_node = graph.GetNode(tensor_id.node());
  return IsSwitch(*input_node);

Patches

We have patched the issue in GitHub commits 0a365c029e437be0349c31f8d4c9926b69fa3fa1 and 045deec1cbdebb27d817008ad5df94d96a08b1bf.

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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.

Record
GHSA-9px9-73fg-3fqp
CVSS 3.1
6.5 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-476
Updated
2026-11-02
Show 5 moreShow less
OSVPYSEC-2026-3154 6.5

Null pointer dereference in Grappler's `IsConstant`

Impact

Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a SavedModel file (fixing the first one would trigger the same dereference in the second place):

First, during constant folding, the GraphDef might not have the required nodes for the binary operation:

  NodeDef* mul_left_child = node_map_->GetNode(node->input(0));
  NodeDef* mul_right_child = node_map_->GetNode(node->input(1));
  // One child must be constant, and the second must be Conv op.
  const bool left_child_is_constant = IsReallyConstant(*mul_left_child);
  const bool right_child_is_constant = IsReallyConstant(*mul_right_child);

If a node is missing, the correposning mul_*child would be null, and the dereference in the subsequent line would be incorrect.

We have a similar issue during IsIdentityConsumingSwitch:

  NodeDef* input_node = graph.GetNode(tensor_id.node());
  return IsSwitch(*input_node);

Patches

We have patched the issue in GitHub commits 0a365c029e437be0349c31f8d4c9926b69fa3fa1 and 045deec1cbdebb27d817008ad5df94d96a08b1bf.

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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.

Record
PYSEC-2026-3154
CVSS 3.1
6.5 MediumCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
OSVBIT-tensorflow-2022-23589 No score

Null pointer dereference in Grappler's `IsConstant` in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a SavedModel file (fixing the first one would trigger the same dereference in the second place). First, during constant folding, the GraphDef might not have the required nodes for the binary operation. If a node is missing, the correposning mul_*child would be null, and the dereference in the subsequent line would be incorrect. We have a similar issue during IsIdentityConsumingSwitch. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Record
BIT-tensorflow-2022-23589
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-2022-153 No score

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a SavedModel file (fixing the first one would trigger the same dereference in the second place). First, during constant folding, the GraphDef might not have the required nodes for the binary operation. If a node is missing, the correposning mul_*child would be null, and the dereference in the subsequent line would be incorrect. We have a similar issue during IsIdentityConsumingSwitch. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Record
PYSEC-2022-153
Updated
2026-11-02
OSVPYSEC-2022-98 No score

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a SavedModel file (fixing the first one would trigger the same dereference in the second place). First, during constant folding, the GraphDef might not have the required nodes for the binary operation. If a node is missing, the correposning mul_*child would be null, and the dereference in the subsequent line would be incorrect. We have a similar issue during IsIdentityConsumingSwitch. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Record
PYSEC-2022-98
Updated
2026-11-02

Affected products

Affected packages

Affected packages
PackageAffectedFixed
tensorflow
PyPI
before 2.5.3
2.5.3
tensorflow
PyPI
2.6.0 up to 2.6.3
2.6.3
tensorflow
PyPI
2.7.0 to 2.7.0
2.7.1
tensorflow-cpu
PyPI
before 2.5.3
2.5.3
tensorflow-cpu
PyPI
2.6.0 up to 2.6.3
2.6.3
tensorflow-cpu
PyPI
2.7.0 to 2.7.0
2.7.1
tensorflow-gpu
PyPI
before 2.5.3
2.5.3
tensorflow-gpu
PyPI
2.6.0 up to 2.6.3
2.6.3
tensorflow-gpu
PyPI
2.7.0 to 2.7.0
2.7.1
tensorflow
Bitnami
before 2.5.3, 2.6.0 up to 2.6.3, 2.7.0 up to 2.7.1
2.5.32.6.32.7.1
Show 12 moreShow less
Affected packages
PackageAffectedFixed
tensorflow
PyPI
before 2.5.3, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 45 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4
2.5.3
tensorflow
PyPI
2.6.0 up to 2.6.3, plus listed versions
2.6.12.6.2
2.6.3
tensorflow
PyPI
2.7.0 up to 2.7.1
2.7.1
tensorflow-cpu
PyPI
before 2.5.3, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 18 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.2
2.5.3
tensorflow-cpu
PyPI
2.6.0 up to 2.6.3, plus listed versions
2.6.12.6.2
2.6.3
tensorflow-cpu
PyPI
2.7.0 up to 2.7.1
2.7.1
tensorflow-gpu
PyPI
before 2.5.3, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 45 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4
2.5.3
tensorflow-gpu
PyPI
2.6.0 up to 2.6.3, plus listed versions
2.6.12.6.2
2.6.3
tensorflow-gpu
PyPI
2.7.0 up to 2.7.1
2.7.1
tensorflow-gpu
PyPI
before 2.5.3, 2.6.0 up to 2.6.3, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 45 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4
2.5.32.6.3
tensorflow-cpu
PyPI
before 2.5.3, 2.6.0 up to 2.6.3, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 20 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.6.12.6.2
2.5.32.6.3
tensorflow
PyPI
before 2.5.3, 2.6.0 up to 2.6.3, 2.7.0 up to 2.7.1, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 45 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4
2.5.32.6.32.7.1

History

History
RecordedChangedSources
facts
first indexedCVE List, EUVD, GitHub Advisories, NVD, OSV

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

In short

CVE-2022-23589 is a medium vulnerability (CVSS 6.5) in Google Tensorflow, published February 4, 2022. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 1.11%, the 66th percentile. Fixed in tensorflow 2.5.3.

References

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