Headline
CVE-2022-35986: Fix RaggedBincount Segmentation Fault from the Splits arg · tensorflow/tensorflow@7a4591f
TensorFlow is an open source platform for machine learning. If RaggedBincount is given an empty input tensor splits, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7a4591fd4f065f4fa903593bc39b2f79530a74b8. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
@@ -734,6 +734,18 @@ def test_size_is_not_scalar(self): # b/206619828
binary_output=False,
name=None))
@test_util.run_in_graph_and_eager_modes
def test_splits_empty(self): # b/238450914
with self.assertRaisesRegex((ValueError, errors.InvalidArgumentError),
“Splits must be non-empty”):
self.evaluate(
gen_math_ops.ragged_bincount(
splits=[], # Invalid splits
values=[1],
size=1,
weights=[1],
binary_output=False,
name=None))
if __name__ == "__main__":
googletest.main()
Related news
### Impact If `RaggedBincount` is given an empty input tensor `splits`, it results in a segfault that can be used to trigger a denial of service attack. ```python import tensorflow as tf binary_output = True splits = tf.random.uniform(shape=[0], minval=-10000, maxval=10000, dtype=tf.int64, seed=-7430) values = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000) size = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000) weights = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.float32, seed=-10000) tf.raw_ops.RaggedBincount(splits=splits, values=values, size=size, weights=weights, binary_output=binary_output) ``` ### Patches We have patched the issue in GitHub commit [7a4591fd4f065f4fa903593bc39b2f79530a74b8](https://github.com/tensorflow/tensorflow/commit/7a4591fd4f065f4fa903593bc39b2f79530a74b8). The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1,...