Sign in
Deutsch English Español Polski
Low

Invalid validation in `SparseMatrixSparseCholesky`

  • Disclosed: 14.05.2021
  • Updated: 11.10.2026 13:19

Impact

An attacker can trigger a null pointer dereference by providing an invalid permutation to tf.raw_ops.SparseMatrixSparseCholesky:

python
import tensorflow as tf
import numpy as np
from tensorflow.python.ops.linalg.sparse import sparse_csr_matrix_ops

indices_array = np.array([[0, 0]])
value_array = np.array([-10.0], dtype=np.float32)
dense_shape = [1, 1]
st = tf.SparseTensor(indices_array, value_array, dense_shape)

input = sparse_csr_matrix_ops.sparse_tensor_to_csr_sparse_matrix(
       st.indices, st.values, st.dense_shape)

permutation = tf.constant([], shape=[1, 0], dtype=tf.int32)
 
tf.raw_ops.SparseMatrixSparseCholesky(input=input, permutation=permutation, type=tf.float32)

This is because the implementation fails to properly validate the input arguments:

cc
void Compute(OpKernelContext* ctx) final {
  ...
  const Tensor& input_permutation_indices = ctx->input(1);
  ...
  ValidateInputs(ctx, *input_matrix, input_permutation_indices, &batch_size, &num_rows);
  ...
}

void ValidateInputs(OpKernelContext* ctx,
    const CSRSparseMatrix& sparse_matrix,
    const Tensor& permutation_indices, int* batch_size,
    int64* num_rows) {
  OP_REQUIRES(ctx, sparse_matrix.dtype() == DataTypeToEnum<T>::value, ...)
  ...
}

Although ValidateInputs is called and there are checks in the body of this function, the code proceeds to the next line in ValidateInputs since OP_REQUIRES is a macro that only exits the current function.

cc
#define OP_REQUIRES(CTX, EXP, STATUS)                     \
  do {                                                    \
    if (!TF_PREDICT_TRUE(EXP)) {                          \
      CheckNotInComputeAsync((CTX), "OP_REQUIRES_ASYNC"); \
      (CTX)->CtxFailure(__FILE__, __LINE__, (STATUS));    \
      return;                                             \
    }                                                     \
  } while (0)

Thus, the first validation condition that fails in ValidateInputs will cause an early return from that function. However, the caller will continue execution from the next line. The fix is to either explicitly check context->status() or to convert ValidateInputs to return a Status.

Patches

We have patched the issue in GitHub commit e6a7c7cc18c3aaad1ae0872cb0a959f5c923d2bd.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 Ying Wang and Yakun Zhang of Baidu X-Team.

Affected software

Click a technology to see all vulnerabilities affecting it.

PlatformPackageVulnerable versionsFixed in
Python (PyPI) tensorflow < 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
Python (PyPI) tensorflow-cpu < 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
Python (PyPI) tensorflow-gpu < 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

References

CVSS score 2.5/10
CVSS vector
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
Weakness (CWE)
CWE-476
Platform
Python (PyPI)
Package
tensorflow, tensorflow-cpu, tensorflow-gpu
Disclosed
14.05.2021
Updated
11.10.2026 13:19

Sources and licenses

OSV / GitHub Advisory Database - PYSEC-2021-167 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - PYSEC-2021-458 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - PYSEC-2021-656 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - GHSA-xcwj-wfcm-m23c - 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
    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. Invalid validation in `SparseMatrixSparseCholesky` this entry
    Low · 2.5 CVE-2021-29530 < 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
  99. 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
  100. Segfault in `tf.quantization.quantize_and_dequantize`
    High · 5.9 CVE-2020-15265 < 2.4.0 2.4.0
  101. 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
  102. Out of bounds access in tensorflow-lite
    Critical · 8.1 CVE-2020-15212 >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 2.2.1, 2.3.1
  103. Segmentation fault in tensorflow-lite
    High · 6.5 CVE-2020-15210 < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  104. Null pointer dereference in tensorflow-lite
    High · 5.9 CVE-2020-15209 < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  105. Data corruption in tensorflow-lite
    High · 7.4 CVE-2020-15208 < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  106. Denial of Service in Tensorflow
    High · 9.0 CVE-2020-15206 < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  107. Denial of Service in Tensorflow
    High · 7.5 CVE-2020-15203 < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  108. Integer truncation in Shard API usage
    High · 9.0 CVE-2020-15202 < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  109. Segfault in Tensorflow
    High · 5.9 CVE-2020-15200 >= 2.3.0, < 2.3.1 2.3.1
  110. Denial of Service in Tensorflow
    High · 5.9 CVE-2020-15199 >= 2.3.0, < 2.3.1 2.3.1
  111. Memory corruption in Tensorflow
    High · 7.1 CVE-2020-15193 >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 2.2.1, 2.3.1
  112. TensorFlow before 1.7.0 has an integer overflow that causes an out-of-bounds read, possibly causing disclosure of the contents of process memory. This occurs in the DecodeBmp feature of the BMP decode
    High · 6.5 CVE-2018-21233 < 1.7.0 1.7.0
  113. Google TensorFlow 1.7.x and earlier is affected by a Buffer Overflow vulnerability. The type of exploitation is context-dependent.
    Critical · 9.8 CVE-2018-7575 < 1.7.1 1.7.1
  114. NULL pointer dereference in Google TensorFlow before 1.12.2 could cause a denial of service via an invalid GIF file.
    High · 6.5 CVE-2019-9635 < 1.12.2 1.12.2
  115. Memcpy parameter overlap in Google Snappy library 1.1.4, as used in Google TensorFlow before 1.7.1, could result in a crash or read from other parts of process memory.
    High · 8.1 CVE-2018-7577 < 1.7.1 1.7.1
  116. Invalid memory access and/or a heap buffer overflow in the TensorFlow XLA compiler in Google TensorFlow before 1.7.1 could cause a crash or read from other parts of process memory via a crafted config
    High · 8.1 CVE-2018-10055 < 1.7.1 1.7.1
  117. Google TensorFlow 1.7 and below is affected by: Buffer Overflow. The impact is: execute arbitrary code (local).
    High · 8.8 CVE-2018-8825 < 1.7.1 1.7.1
  118. Google TensorFlow 1.6.x and earlier is affected by: Null Pointer Dereference. The type of exploitation is: context-dependent.
    High · 6.5 CVE-2018-7576 < 1.7.0rc0 1.7.0rc0

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.