GitHub Advisoryadvisory · PyPI
GHSA-pqhm-4wvf-2jg8 Missing validation results in undefined behavior in `QuantizedConv2D`
MEDIUM
Official page ↗
- Aliases
- CVE-2022-29201
- 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, CWE-476
- 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.QuantizedConv2D` does not fully validate the input arguments:
```python
import tensorflow as tf
input = tf.constant(1, shape=[1, 2, 3, 3], dtype=tf.quint8)
filter = tf.constant(1, shape=[1, 2, 3, 3], dtype=tf.quint8)
bad args
min_input = tf.constant([], shape=[0], dtype=tf.float32)
max_input = tf.constant(0, shape=[], dtype=tf.float32)
min_filter = tf.constant(0, shape=[], dtype=tf.float32)
max_filter = tf.constant(0, shape=[], dtype=tf.float32)
tf.raw_ops.QuantizedConv2D(
input=input,
filter=filter,
min_input=min_input,
max_input=max_input,
min_filter=min_filter,
max_filter=max_filter,
strides=[1, 1, 1, 1],
padding="SAME")
```
In this case, references get bound to `nullptr` for each argument that is empty (in the example, all arguments in the `bad args` section).
Patches
We have patched the issue in GitHub commit 0f0b080ecde4d3dfec158d6f60da34d5e31693c4.
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-2022-29201 TensorFlow is an open source platform for machine learning. vulnerability
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pqhm-4wvf-2jg8 web
- https://nvd.nist.gov/vuln/detail/CVE-2022-29201 advisory
- https://github.com/tensorflow/tensorflow/commit/0f0b080ecde4d3dfec158d6f60da34d5e31693c4 web
- https://github.com/tensorflow/tensorflow package
- https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/quantized_conv_ops.cc 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