chore: import upstream snapshot with attribution

2026-07-13 12:14:16 +08:00
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+## TFSA-2022-150: Overflow in `tf.keras.losses.poisson`
+
+### CVE Number
+CVE-2022-41887
+
+### Impact
+[`tf.keras.losses.poisson`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/keras/losses.py) receives a `y_pred` and `y_true` that are passed through `functor::mul` in [`BinaryOp`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/cwise_ops_common.h). If the resulting dimensions overflow an `int32`, TensorFlow will crash due to a size mismatch during broadcast assignment.
+```python
+import numpy as np
+import tensorflow as tf
+
+true_value = tf.reshape(shape=[1, 2500000000], tensor = tf.zeros(dtype=tf.bool, shape=[50000, 50000]))
+pred_value = np.array([[[-2]], [[8]]], dtype = np.float64)
+
+tf.keras.losses.poisson(y_true=true_value,y_pred=pred_value)
+```
+
+### Patches
+We have patched the issue in GitHub commit [c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c](https://github.com/tensorflow/tensorflow/commit/c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c).
+
+The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 and 2.9.3, as these are also affected and still in supported range. However, we will not cherrypick this commit into TensorFlow 2.8.x, as it depends on Eigen behavior that changed between 2.8 and 2.9.
+
+
+### For more information
+Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
+
+
+### Attribution
+This vulnerability has been reported by Pattarakrit Rattankul.