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High

Undefined behavior via `nullptr` reference binding in sparse matrix multiplication

  • Disclosed: 05.11.2021
  • Updated: 11.10.2026 13:19

Impact

The code for sparse matrix multiplication is vulnerable to undefined behavior via binding a reference to nullptr:

python
import tensorflow as tf
  
tf.raw_ops.SparseMatMul(
  a=[[1.0,1.0,1.0]],
  b=[[],[],[]],
  transpose_a=False,
  transpose_b=False,
  a_is_sparse=False, 
  b_is_sparse=True)

This occurs whenever the dimensions of a or b are 0 or less. In the case on one of these is 0, an empty output tensor should be allocated (to conserve the invariant that output tensors are always allocated when the operation is successful) but nothing should be written to it (that is, we should return early from the kernel implementation). Otherwise, attempts to write to this empty tensor would result in heap OOB access.

Patches

We have patched the issue in GitHub commit e6cf28c72ba2eb949ca950d834dd6d66bb01cfae.

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 members of the Aivul Team from Qihoo 360.

Affected software

Click a technology to see all vulnerabilities affecting it.

PlatformPackageVulnerable versionsFixed in
Python (PyPI) tensorflow >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
Python (PyPI) tensorflow-cpu >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
Python (PyPI) tensorflow-gpu >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4

References

CVSS score 7.8/10
CVSS vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Weakness (CWE)
CWE-125, CWE-824
Platform
Python (PyPI)
Package
tensorflow, tensorflow-cpu, tensorflow-gpu
Disclosed
05.11.2021
Updated
11.10.2026 13:19

Sources and licenses

OSV / GitHub Advisory Database - PYSEC-2021-411 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - PYSEC-2021-628 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - PYSEC-2021-826 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - GHSA-4f99-p9c2-3j8x - CC BY 4.0

Vulnerability history: tensorflow-cpu

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 (430) in the archive
Total entries
430
First → latest
04.2019 07.2024
Without a fix
0
Exploited in attacks
0

Severity breakdown

  • Critical 6
  • High 111
  • Medium 208
  • 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. 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
  24. 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
  25. 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
  26. 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
  27. 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
  28. 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
  29. Out of bounds read in Tensorflow
    High · 8.8 CVE-2022-23594 >= 2.7.0, < 2.7.1 2.7.1
  30. Read and Write outside of bounds in TensorFlow
    High · 8.8 CVE-2022-23560 < 2.5.3, >= 2.6.0, < 2.6.3 2.5.3, 2.6.3
  31. Insecure temporary file in Tensorflow
    High · 7.1 CVE-2022-23563 < 2.5.3, >= 2.6.0, < 2.6.3 2.5.3, 2.6.3
  32. Out of bounds read in Tensorflow
    High · 8.1 CVE-2022-23592 >= 2.7.0, < 2.8.0 2.8.0
  33. Stack overflow in TensorFlow
    High · 7.5 CVE-2022-23591 < 2.5.3, >= 2.6.0, < 2.6.3 2.5.3, 2.6.3
  34. Out of bounds read and write in Tensorflow
    High · 8.8 CVE-2022-23574 < 2.5.3, >= 2.6.0, < 2.6.3 2.5.3, 2.6.3
  35. Uninitialized variable access in Tensorflow
    High · 7.6 CVE-2022-23573 < 2.5.3, >= 2.6.0, < 2.6.3 2.5.3, 2.6.3
  36. Integer overflow in Tensorflow
    High · 7.6 CVE-2022-23562 < 2.5.3, >= 2.6.0, < 2.6.3 2.5.3, 2.6.3
  37. Out of bounds write in TFLite
    High · 8.8 CVE-2022-23561 < 2.5.3, >= 2.6.0, < 2.6.3 2.5.3, 2.6.3
  38. Integer overflow in TFLite
    High · 8.8 CVE-2022-23559 < 2.5.3, >= 2.6.0, < 2.6.3 2.5.3, 2.6.3
  39. Out of bounds write in Tensorflow
    High · 8.8 CVE-2022-23566 < 2.5.3, >= 2.6.0, < 2.6.3 2.5.3, 2.6.3
  40. Use after free in `DecodePng` kernel
    High · 7.6 CVE-2022-23584 < 2.5.3, >= 2.6.0, < 2.6.3 2.5.3, 2.6.3
  41. Integer overflow in TFLite array creation
    High · 7.6 CVE-2022-23558 < 2.5.3, >= 2.6.0, < 2.6.3 2.5.3, 2.6.3
  42. Integer overflow in TensorFlow
    High · 8.8 CVE-2022-23587 < 2.5.3, >= 2.6.0, < 2.6.3 2.5.3, 2.6.3
  43. Heap overflow in Tensorflow
    High · 7.6 CVE-2022-21740 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  44. Division by zero in TFLite
    High · 6.5 CVE-2022-21741 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  45. Null pointer dereference in TensorFlow
    High · 6.5 CVE-2022-21739 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  46. Assertion failure based denial of service in Tensorflow
    High · 6.5 CVE-2022-21737 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  47. Integer overflow leading to crash in Tensorflow
    High · 6.5 CVE-2022-21738 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  48. `CHECK`-fails when building invalid tensor shapes in Tensorflow
    High · 6.5 CVE-2022-23569 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  49. Overflow and uncaught divide by zero in Tensorflow
    High · 6.5 CVE-2022-21729 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  50. `CHECK`-failures in Tensorflow
    High · 6.5 CVE-2022-21734 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  51. Division by zero in Tensorflow
    High · 6.5 CVE-2022-21735 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  52. Undefined behavior in `SparseTensorSliceDataset`
    High · 7.6 CVE-2022-21736 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  53. Type confusion leading to segfault in Tensorflow
    High · 6.5 CVE-2022-21731 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  54. Integer overflows in Tensorflow
    High · 6.5 CVE-2022-23567 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  55. Integer overflows in Tensorflow
    High · 6.5 CVE-2022-23568 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  56. Out of bounds read in Tensorflow
    High · 8.1 CVE-2022-21726 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  57. Out of bounds read in Tensorflow
    High · 8.1 CVE-2022-21728 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  58. Integer overflow in Tensorflow
    High · 7.6 CVE-2022-21727 < 2.5.3, >= 2.6.0, < 2.6.3 2.5.3, 2.6.3
  59. Out of bounds read in Tensorflow
    High · 8.1 CVE-2022-21730 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  60. Access to invalid memory during shape inference in `Cudnn*` ops
    High · 7.8 CVE-2021-41221 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  61. Use after free / memory leak in `CollectiveReduceV2`
    High · 7.8 CVE-2021-41220 >= 2.6.0, < 2.6.1 2.6.1
  62. Incomplete validation in boosted trees code
    Critical · 9.3 CVE-2021-41208 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  63. Incomplete validation of shapes in multiple TF ops
    High · 7.0 CVE-2021-41206 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  64. Undefined behavior via `nullptr` reference binding in sparse matrix multiplication this entry
    High · 7.8 CVE-2021-41219 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  65. Reference binding to `nullptr` in `tf.ragged.cross`
    High · 7.8 CVE-2021-41214 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  66. Heap OOB read in `tf.ragged.cross`
    High · 7.1 CVE-2021-41212 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  67. Heap OOB in shape inference for `QuantizeV2`
    High · 7.1 CVE-2021-41211 >= 2.6.0, < 2.6.1 2.6.1
  68. Missing validation during checkpoint loading
    High · 7.8 CVE-2021-41203 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  69. Heap OOB read in `tf.raw_ops.SparseCountSparseOutput`
    High · 7.1 CVE-2021-41210 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  70. Unitialized access in `EinsumHelper::ParseEquation`
    High · 7.8 CVE-2021-41201 >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 2.6.1, 2.5.2, 2.4.4
  71. Heap OOB in nested `tf.map_fn` with `RaggedTensor`s
    High · 7.1 CVE-2021-37679 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  72. Arbitrary code execution due to YAML deserialization
    High · 9.3 CVE-2021-37678 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  73. Incomplete validation in MKL requantization
    High · 7.8 CVE-2021-37665 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  74. Incomplete validation in `QuantizeV2`
    High · 7.8 CVE-2021-37663 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  75. Null pointer dereference in TFLite MLIR optimizations
    High · 7.8 CVE-2021-37689 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  76. Null pointer dereference in TFLite
    High · 7.8 CVE-2021-37688 >= 2.5.0, < 2.5.1, >= 2.4.0, < 2.4.3, < 2.3.4 2.5.1, 2.4.3, 2.3.4
  77. NPE in TFLite
    High · 7.8 CVE-2021-37681 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  78. Reference binding to nullptr in shape inference
    High · 7.8 CVE-2021-37676 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  79. Reference binding to nullptr in map operations
    High · 7.8 CVE-2021-37671 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  80. Reference binding to nullptr in unicode encoding
    High · 7.8 CVE-2021-37667 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  81. Reference binding to nullptr in `RaggedTensorToVariant`
    High · 7.8 CVE-2021-37666 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  82. Use after free in boosted trees creation
    High · 7.8 CVE-2021-37652 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  83. Incorrect validation of `SaveV2` inputs
    High · 7.8 CVE-2021-37648 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  84. Heap OOB in boosted trees
    High · 7.3 CVE-2021-37664 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  85. Reference binding to nullptr and heap OOB in binary cwise ops
    High · 7.3 CVE-2021-37659 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  86. Heap OOB in `ResourceScatterUpdate`
    High · 7.3 CVE-2021-37655 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  87. Heap OOB and CHECK fail in `ResourceGather`
    High · 7.3 CVE-2021-37654 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  88. Heap buffer overflow in `FractionalAvgPoolGrad`
    High · 7.1 CVE-2021-37651 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  89. Segfault and heap buffer overflow in `{Experimental,}DatasetToTFRecord`
    High · 7.8 CVE-2021-37650 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  90. Heap out of bounds access in sparse reduction operations
    High · 7.3 CVE-2021-37635 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  91. Null pointer dereference in `UncompressElement`
    High · 7.7 CVE-2021-37649 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  92. Null pointer dereference in `SparseTensorSliceDataset`
    High · 7.7 CVE-2021-37647 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  93. Null pointer dereference in `MatrixDiagPartOp`
    High · 7.7 CVE-2021-37643 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  94. Null pointer dereference and heap OOB read in operations restoring tensors
    High · 8.4 CVE-2021-37639 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  95. Null pointer dereference in `RaggedTensorToTensor`
    High · 7.7 CVE-2021-37638 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  96. Null pointer dereference in `CompressElement`
    High · 7.7 CVE-2021-37637 < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1 2.3.4, 2.4.3, 2.5.1
  97. Stack overflow due to looping TFLite subgraph
    High · 7.3 CVE-2021-29591 < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 2.1.4, 2.2.3, 2.3.3, 2.4.2
  98. TensorFlow vulnerable to heap out of bounds read in filesystem glob matching
    High · 9.1 CVE-2020-26269 >= 2.4.0rc0, < 2.4.0 2.4.0
  99. Segfault in `tf.quantization.quantize_and_dequantize`
    High · 5.9 CVE-2020-15265 < 2.4.0 2.4.0
  100. Out of bounds write in tensorflow-lite
    Critical · 8.1 CVE-2020-15214 >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 2.2.1, 2.3.1
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Important vulnerabilities, actionable guidance and practical advice for your applications. Choose your technologies and follow what matters to your project.

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