Sign in
Deutsch English Español Polski
Medium

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

  • Disclosed: 16.09.2022
  • Updated: 11.10.2026 14:17

Impact

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

cpp
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.

Affected software

Click a technology to see all vulnerabilities affecting it.

PlatformPackageVulnerable versionsFixed in
Python (PyPI) tensorflow < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 2.7.2, 2.8.1, 2.9.1
Python (PyPI) tensorflow-cpu < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 2.7.2, 2.8.1, 2.9.1
Python (PyPI) tensorflow-gpu < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 2.7.2, 2.8.1, 2.9.1

References

CVSS score 5.9/10
CVSS vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness (CWE)
CWE-476
Platform
Python (PyPI)
Package
tensorflow, tensorflow-cpu, tensorflow-gpu
Disclosed
16.09.2022
Updated
11.10.2026 14:17

Sources and licenses

OSV / GitHub Advisory Database - PYSEC-2026-3132 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - PYSEC-2026-3295 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - GHSA-828c-5j5q-vrjq - CC BY 4.0

OSV / GitHub Advisory Database - PYSEC-2026-968 - PyPA Advisory Database; CC BY 4.0

Vulnerability history: tensorflow

All published vulnerabilities of this package (Python (PyPI)), newest first. Shows whether this is a one-off slip or a package that needs watching.

All (433) in the archive
Total entries
433
First → latest
04.2019 07.2024
Without a fix
0
Exploited in attacks
0

Severity breakdown

  • Critical 6
  • High 112
  • Medium 210
  • Low 105

Disclosures per year

Severity:
  1. TensorFlow has segfault in array_ops.upper_bound
    High · 7.5 CVE-2023-33976 < 2.12.1 2.12.1
  2. TensorFlow vulnerable to Out-of-Bounds Read in DynamicStitch
    High · 7.5 CVE-2023-25659 < 2.11.1 2.11.1
  3. TensorFlow vulnerable to seg fault in `tf.raw_ops.Print`
    High · 7.5 CVE-2023-25660 < 2.11.1 2.11.1
  4. TensorFlow vulnerable to integer overflow in EditDistance
    High · 7.5 CVE-2023-25662 < 2.11.1 2.11.1
  5. TensorFlow has Null Pointer Error in TensorArrayConcatV2
    High · 7.5 CVE-2023-25663 < 2.11.1 2.11.1
  6. TensorFlow has Heap-buffer-overflow in AvgPoolGrad
    High · 7.5 CVE-2023-25664 < 2.11.1 2.11.1
  7. TensorFlow has Null Pointer Error in SparseSparseMaximum
    High · 7.5 CVE-2023-25665 < 2.11.1 2.11.1
  8. TensorFlow has Floating Point Exception in AudioSpectrogram
    High · 7.5 CVE-2023-25666 < 2.11.1 2.11.1
  9. TensorFlow has a heap out-of-buffer read vulnerability in the QuantizeAndDequantize operation
    Critical · 9.8 CVE-2023-25668 < 2.11.1 2.11.1
  10. TensorFlow has Floating Point Exception in AvgPoolGrad with XLA
    High · 7.5 CVE-2023-25669 < 2.11.1 2.11.1
  11. TensorFlow has Null Pointer Error in QuantizedMatMulWithBiasAndDequantize
    High · 7.5 CVE-2023-25670 < 2.11.1 2.11.1
  12. TensorFlow has segmentation fault in tfg-translate
    High · 7.5 CVE-2023-25671 < 2.11.1 2.11.1
  13. TensorFlow has Null Pointer Error in LookupTableImportV2
    High · 7.5 CVE-2023-25672 < 2.11.1 2.11.1
  14. TensorFlow has Floating Point Exception in TensorListSplit with XLA
    High · 7.5 CVE-2023-25673 < 2.11.1 2.11.1
  15. TensorFlow has Null Pointer Error in RandomShuffle with XLA enable
    High · 7.5 CVE-2023-25674 < 2.11.1 2.11.1
  16. TensorFlow has Segfault in Bincount with XLA
    High · 7.5 CVE-2023-25675 < 2.11.1 2.11.1
  17. TensorFlow has null dereference on ParallelConcat with XLA
    High · 7.5 CVE-2023-25676 < 2.11.1 2.11.1
  18. TensorFlow has double free in Fractional(Max/Avg)Pool
    High · 8.0 CVE-2023-25801 < 2.11.1 2.11.1
  19. TensorFlow has Floating Point Exception in TFLite in conv kernel
    High · 7.5 CVE-2023-27579 < 2.11.1 2.11.1
  20. TensorFlow vulnerable to Out-of-Bounds Read in GRUBlockCellGrad
    High · 7.5 CVE-2023-25658 < 2.11.1 2.11.1
  21. Out of bounds write in grappler in Tensorflow
    High · 7.1 CVE-2022-41902 < 2.8.4, >= 2.9.0, < 2.9.3, >= 2.10.0, < 2.10.1 2.8.4, 2.9.3, 2.10.1
  22. FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess
    High · 7.1 CVE-2022-41900 < 2.8.4, >= 2.9.0, < 2.9.3, >= 2.10.0, < 2.10.1 2.8.4, 2.9.3, 2.10.1
  23. Buffer overflow in `CONV_3D_TRANSPOSE` on TFLite
    High · 7.1 CVE-2022-41894 < 2.8.4, >= 2.9.0, < 2.9.3, >= 2.10.0, < 2.10.1 2.8.4, 2.9.3, 2.10.1
  24. TensorFlow vulnerable to null-dereference in `mlir::tfg::GraphDefImporter::ConvertNodeDef` this entry
    Medium · 5.9 CVE-2022-36013 < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 2.7.2, 2.8.1, 2.9.1
  25. TensorFlow vulnerable to OOB write in `scatter_nd` in TF Lite
    High · 7.0 CVE-2022-35939 < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 2.7.2, 2.8.1, 2.9.1
  26. TensorFlow vulnerable to OOB read in `Gather_nd` in TF Lite
    High · 7.0 CVE-2022-35937 < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 2.7.2, 2.8.1, 2.9.1
  27. Code injection in `saved_model_cli` in TensorFlow
    High · 7.8 CVE-2022-29216 < 2.6.4, >= 2.7.0, < 2.7.2, >= 2.8.0, < 2.8.1 2.6.4, 2.7.2, 2.8.1
  28. Segfault and OOB write due to incomplete validation in `EditDistance` in TensorFlow
    High · 7.1 CVE-2022-29208 < 2.6.4, >= 2.7.0, < 2.7.2, >= 2.8.0, < 2.8.1 2.6.4, 2.7.2, 2.8.1
  29. NULL Pointer Dereference and Access of Uninitialized Pointer in TensorFlow
    Critical · 9.3 ghsa-h6gw-r52c-724r < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  30. Improper Validation of Integrity Check Value in TensorFlow
    High · 7.0 ghsa-43q8-3fv7-pr5x < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  31. Out of bounds read in Tensorflow
    High · 8.8 CVE-2022-23594 >= 2.7.0, < 2.7.1 2.7.1
  32. Read and Write outside of bounds in TensorFlow
    High · 8.8 CVE-2022-23560 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  33. Insecure temporary file in Tensorflow
    High · 7.1 CVE-2022-23563 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  34. Out of bounds read in Tensorflow
    High · 8.1 CVE-2022-23592 >= 2.8.0-rc0, < 2.8.0 2.8.0
  35. Stack overflow in TensorFlow
    High · 7.5 CVE-2022-23591 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  36. Out of bounds read and write in Tensorflow
    High · 8.8 CVE-2022-23574 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  37. Uninitialized variable access in Tensorflow
    High · 7.6 CVE-2022-23573 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  38. Integer overflow in Tensorflow
    High · 7.6 CVE-2022-23562 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  39. Out of bounds write in TFLite
    High · 8.8 CVE-2022-23561 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  40. Integer overflow in TFLite
    High · 8.8 CVE-2022-23559 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
Show more (20) Showing 40 of 119

Know which vulnerabilities affect your application

With the DockRay integration and software inventory enabled, DockRay checks reported component versions against known vulnerabilities and notifies you about confirmed matches. Coverage depends on the supported technology and available advisory data.

Connect your application
DockRay newsletter

Application security in your inbox

Important vulnerabilities, actionable guidance and practical advice for your applications. Choose your technologies and follow what matters to your project.

  • A daily digest of new vulnerabilities, critical ones included.
  • Notifications about important updates.
  • Practical advice on application security and monitoring.

Leave empty to receive updates for every technology.

Privacy policy

Free to subscribe. Unsubscribe with one click in any email.