QID 981543
QID 981543: Python (pip) Security Update for tensorflow-gpu (GHSA-7ghq-fvr3-pj2x)
Security update has been released for tensorflow-gpu,tensorflow,tensorflow-cpu to fix the vulnerability.
Note: The preceding description block is extracted directly from the security advisory. Using automation, we have attempted to clean and format it as much as possible without introducing additional issues.
An attacker can trigger a denial of service via a segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation:
```python
import tensorflow as tf
tf.raw_ops.MaxPoolGrad(
orig_input = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32),
orig_output = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32),
grad = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32),
ksize = [1, 16, 16, 1],
strides = [1, 16, 18, 1],
padding = "EXPLICIT",
explicit_paddings = [0, 0, 14, 3, 15, 5, 0, 0])
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors.
The fixes for [CVE-2021-29579](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-068.md) were incomplete.
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
- GHSA-7ghq-fvr3-pj2x -
github.com/advisories/GHSA-7ghq-fvr3-pj2x
CVEs related to QID 981543
| Advisory ID | Software | Component | Link |
|---|---|---|---|
| GHSA-7ghq-fvr3-pj2x | tensorflow |
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| GHSA-7ghq-fvr3-pj2x | tensorflow-cpu |
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| GHSA-7ghq-fvr3-pj2x | tensorflow-gpu |
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