chore: import upstream snapshot with attribution

2026-07-13 12:14:16 +08:00
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+## TFSA-2021-150: Division by 0 in most convolution operators
+
+### CVE Number
+CVE-2021-37675
+
+### Impact
+Most implementations of convolution operators in TensorFlow are affected by a
+division by 0 vulnerability where an attacker can trigger a denial of service
+via a crash:
+
+```python
+import tensorflow as tf
+
+tf.compat.v1.disable_v2_behavior()
+tf.raw_ops.Conv2D(
+  input = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32),
+  filter = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32),
+  strides = [1, 1, 1, 1],
+  padding = "SAME")
+```
+
+The shape inference
+[implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/framework/common_shape_fns.cc#L577)
+is missing several validations before doing divisions and modulo operations.
+
+### Patches
+We have patched the issue in GitHub commit
+[8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4](https://github.com/tensorflow/tensorflow/commit/8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4).
+
+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.
+
+### 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 Yakun Zhang of Baidu Security.