QID 981541
QID 981541: Python (pip) Security Update for tensorflow-gpu (GHSA-5hj3-vjjf-f5m7)
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 read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.SdcaOptimizerV2`:
```python
import tensorflow as tf
tf.raw_ops.SdcaOptimizerV2(
sparse_example_indices=[[1]],
sparse_feature_indices=[[1]],
sparse_feature_values=[[1.0,2.0]],
dense_features=[[1.0]],
example_weights=[1.0],
example_labels=[],
sparse_indices=[1],
sparse_weights=[1.0],
dense_weights=[[1.0]],
example_state_data=[[100.0,100.0,100.0,100.0]],
loss_type='logistic_loss',
l1=100.0,
l2=100.0,
num_loss_partitions=1,
num_inner_iterations=1,
adaptive=True)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/sdca_internal.cc#L320-L353) does not check that the length of `example_labels` is the same as the number of examples.
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-5hj3-vjjf-f5m7 -
github.com/advisories/GHSA-5hj3-vjjf-f5m7
CVEs related to QID 981541
| Advisory ID | Software | Component | Link |
|---|---|---|---|
| GHSA-5hj3-vjjf-f5m7 | tensorflow |
|
|
| GHSA-5hj3-vjjf-f5m7 | tensorflow-cpu |
|
|
| GHSA-5hj3-vjjf-f5m7 | tensorflow-gpu |
|