CVE-2022-36013

Null-dereference in `mlir::tfg::GraphDefImporter::ConvertNodeDef` in TensorFlow

5.9 MediumFix available

TensorFlow is an open source platform for machine learning. When mlir::tfg::GraphDefImporter::ConvertNodeDef tries to convert NodeDefs without an op name, it crashes. We have patched the issue in GitHub commit a0f0b9a21c9270930457095092f558fbad4c03e5. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

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: None
Integrity: None
Availability: High

Exploit likelihood

0.70%Down 0.2 points since Sep 17, 2022

What each source reports

CVE List Score used 5.9

Null-dereference in `mlir::tfg::GraphDefImporter::ConvertNodeDef` in TensorFlow

Record: CVE-2022-36013
CVSS 3.1: 5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness: CWE-476
Updated: 2026-11-02

EUVDEUVD-2022-6737 5.9

Record: EUVD-2022-6737
CVSS 3.1: 5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated: 2026-11-02

GitHub AdvisoriesGHSA-828c-5j5q-vrjq 5.9

TensorFlow vulnerable to null-dereference in `mlir::tfg::GraphDefImporter::ConvertNodeDef`

Impact

When mlir::tfg::GraphDefImporter::ConvertNodeDef tries to convert NodeDefs without an op name, it crashes.

Status GraphDefImporter::ConvertNodeDef(OpBuilder &builder, ConversionState &s,
                                        const NodeDef &node) {
  VLOG(4) << "Importing: " << node.name();
  OperationState state(ConvertLocation(node), absl::StrCat("tfg.", node.op()));

  // The GraphImporter does light shape inference, but here we will defer all of
  // that to the shape inference pass.
  const OpDef *op_def;
  const OpRegistrationData *op_reg_data = nullptr;
  if ((op_reg_data = registry_.LookUp(node.op()))) {
    op_def = &op_reg_data->op_def;
  } else {
    auto it = function_op_defs_.find(node.op());
    if (it == function_op_defs_.end())
      return InvalidArgument("Unable to find OpDef for ", node.op());
    op_def = it->second;
  }

node.op().empty() cannot be empty.

Patches

We have patched the issue in GitHub commit a0f0b9a21c9270930457095092f558fbad4c03e5.

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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-828c-5j5q-vrjq
CVSS 3.1: 5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness: CWE-476
Updated: 2026-11-02

NVD 5.9

Record: CVE-2022-36013
CVSS 3.1: 5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
CVSS 3.1: 7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness: CWE-476
Updated: 2026-11-02

OSV 5.9

Null-dereference in `mlir::tfg::GraphDefImporter::ConvertNodeDef` in TensorFlow

Record: CVE-2022-36013
CVSS 3.1: 5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness: CWE-476
Updated: 2026-11-02

OSVGHSA-828c-5j5q-vrjq 5.9

TensorFlow vulnerable to null-dereference in `mlir::tfg::GraphDefImporter::ConvertNodeDef`

Impact

When mlir::tfg::GraphDefImporter::ConvertNodeDef tries to convert NodeDefs without an op name, it crashes.

Status GraphDefImporter::ConvertNodeDef(OpBuilder &builder, ConversionState &s,
                                        const NodeDef &node) {
  VLOG(4) << "Importing: " << node.name();
  OperationState state(ConvertLocation(node), absl::StrCat("tfg.", node.op()));

  // The GraphImporter does light shape inference, but here we will defer all of
  // that to the shape inference pass.
  const OpDef *op_def;
  const OpRegistrationData *op_reg_data = nullptr;
  if ((op_reg_data = registry_.LookUp(node.op()))) {
    op_def = &op_reg_data->op_def;
  } else {
    auto it = function_op_defs_.find(node.op());
    if (it == function_op_defs_.end())
      return InvalidArgument("Unable to find OpDef for ", node.op());
    op_def = it->second;
  }

node.op().empty() cannot be empty.

Patches

We have patched the issue in GitHub commit a0f0b9a21c9270930457095092f558fbad4c03e5.

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-828c-5j5q-vrjq
CVSS 3.1: 5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness: CWE-476
Updated: 2026-11-02

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OSVPYSEC-2026-3132 5.9

TensorFlow vulnerable to null-dereference in `mlir::tfg::GraphDefImporter::ConvertNodeDef`

Impact

When mlir::tfg::GraphDefImporter::ConvertNodeDef tries to convert NodeDefs without an op name, it crashes.

Status GraphDefImporter::ConvertNodeDef(OpBuilder &builder, ConversionState &s,
                                        const NodeDef &node) {
  VLOG(4) << "Importing: " << node.name();
  OperationState state(ConvertLocation(node), absl::StrCat("tfg.", node.op()));

  // The GraphImporter does light shape inference, but here we will defer all of
  // that to the shape inference pass.
  const OpDef *op_def;
  const OpRegistrationData *op_reg_data = nullptr;
  if ((op_reg_data = registry_.LookUp(node.op()))) {
    op_def = &op_reg_data->op_def;
  } else {
    auto it = function_op_defs_.find(node.op());
    if (it == function_op_defs_.end())
      return InvalidArgument("Unable to find OpDef for ", node.op());
    op_def = it->second;
  }

node.op().empty() cannot be empty.

Patches

We have patched the issue in GitHub commit a0f0b9a21c9270930457095092f558fbad4c03e5.

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-2026-3132
CVSS 3.1: 5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated: 2026-11-02

OSVPYSEC-2026-3295 5.9

TensorFlow vulnerable to null-dereference in `mlir::tfg::GraphDefImporter::ConvertNodeDef`

Impact

When mlir::tfg::GraphDefImporter::ConvertNodeDef tries to convert NodeDefs without an op name, it crashes.

Status GraphDefImporter::ConvertNodeDef(OpBuilder &builder, ConversionState &s,
                                        const NodeDef &node) {
  VLOG(4) << "Importing: " << node.name();
  OperationState state(ConvertLocation(node), absl::StrCat("tfg.", node.op()));

  // The GraphImporter does light shape inference, but here we will defer all of
  // that to the shape inference pass.
  const OpDef *op_def;
  const OpRegistrationData *op_reg_data = nullptr;
  if ((op_reg_data = registry_.LookUp(node.op()))) {
    op_def = &op_reg_data->op_def;
  } else {
    auto it = function_op_defs_.find(node.op());
    if (it == function_op_defs_.end())
      return InvalidArgument("Unable to find OpDef for ", node.op());
    op_def = it->second;
  }

node.op().empty() cannot be empty.

Patches

We have patched the issue in GitHub commit a0f0b9a21c9270930457095092f558fbad4c03e5.

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-2026-3295
CVSS 3.1: 5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated: 2026-11-02

OSVPYSEC-2026-968 5.9

TensorFlow vulnerable to null-dereference in `mlir::tfg::GraphDefImporter::ConvertNodeDef`

Impact

When mlir::tfg::GraphDefImporter::ConvertNodeDef tries to convert NodeDefs without an op name, it crashes.

Status GraphDefImporter::ConvertNodeDef(OpBuilder &builder, ConversionState &s,
                                        const NodeDef &node) {
  VLOG(4) << "Importing: " << node.name();
  OperationState state(ConvertLocation(node), absl::StrCat("tfg.", node.op()));

  // The GraphImporter does light shape inference, but here we will defer all of
  // that to the shape inference pass.
  const OpDef *op_def;
  const OpRegistrationData *op_reg_data = nullptr;
  if ((op_reg_data = registry_.LookUp(node.op()))) {
    op_def = &op_reg_data->op_def;
  } else {
    auto it = function_op_defs_.find(node.op());
    if (it == function_op_defs_.end())
      return InvalidArgument("Unable to find OpDef for ", node.op());
    op_def = it->second;
  }

node.op().empty() cannot be empty.

Patches

We have patched the issue in GitHub commit a0f0b9a21c9270930457095092f558fbad4c03e5.

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-2026-968
CVSS 3.1: 5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated: 2026-11-02

OSVBIT-tensorflow-2022-36013 No score

Null-dereference in `mlir::tfg::GraphDefImporter::ConvertNodeDef` in TensorFlow

Record: BIT-tensorflow-2022-36013
Updated: 2026-11-02

OSVopenSUSE-SU-2024:12355-1 No score

tensorflow-lite-2.10.0-1.1 on GA media

These are all security issues fixed in the tensorflow-lite-2.10.0-1.1 package on the GA media of openSUSE Tumbleweed.

Record: openSUSE-SU-2024:12355-1
Updated: 2026-11-02

Affected products

Affected packages

Affected packages
Package	Affected	Fixed
`tensorflow` PyPI	before 2.7.2	2.7.2
`tensorflow` PyPI	2.8.0 up to 2.8.1	2.8.1
`tensorflow` PyPI	2.9.0 up to 2.9.1	2.9.1
`tensorflow-cpu` PyPI	before 2.7.2	2.7.2
`tensorflow-cpu` PyPI	2.8.0 up to 2.8.1	2.8.1
`tensorflow-cpu` PyPI	2.9.0 up to 2.9.1	2.9.1
`tensorflow-gpu` PyPI	before 2.7.2	2.7.2
`tensorflow-gpu` PyPI	2.8.0 up to 2.8.1	2.8.1
`tensorflow-gpu` PyPI	2.9.0 up to 2.9.1	2.9.1
`tensorflow` Bitnami	before 2.7.2, 2.8.0 up to 2.8.1, 2.9.0 up to 2.9.1	2.7.22.8.12.9.1

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Affected packages
Package	Affected	Fixed
`tensorflow` PyPI	before 2.7.2, 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	2.7.2
`tensorflow-cpu` PyPI	before 2.7.2, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 Show 27 moreShow less 2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.6.42.6.52.7.02.7.1	2.7.2
`tensorflow-gpu` PyPI	before 2.7.2, 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	2.7.2
`tensorflow` PyPI	before 2.7.2, 2.8.0 up to 2.8.1, 2.9.0 up to 2.9.1, 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	2.7.22.8.12.9.1
`tensorflow-cpu` PyPI	before 2.7.2, 2.8.0 up to 2.8.1, 2.9.0 up to 2.9.1, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 Show 27 moreShow less 2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.6.42.6.52.7.02.7.1	2.7.22.8.12.9.1
`tensorflow-gpu` PyPI	before 2.7.2, 2.8.0 up to 2.8.1, 2.9.0 up to 2.9.1, 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	2.7.22.8.12.9.1

History

History
Recorded	Changed	Sources
Nov 6, 2026	facts
Nov 2, 2026	first indexed	CVE List, EUVD, GitHub Advisories, NVD, OSV

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

In short

CVE-2022-36013 is a medium vulnerability (CVSS 5.9) in Google Tensorflow, published September 16, 2022. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.70%, the 53rd percentile. Fixed in tensorflow 2.7.2.

References

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This page doesn't list everything

Left out here: 82 versions. The JSON record has them.