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PYSEC-2026-3376
No affected components available
Impact
tf.raw_ops.DynamicStitch specifies input sizes when it is registered.
REGISTER_OP("DynamicStitch")
.Input("indices: N * int32")
.Input("data: N * T")
.Output("merged: T")
.Attr("N : int >= 1")
.Attr("T : type")
.SetShapeFn(DynamicStitchShapeFunction);
When it receives a differing number of inputs, such as when it is called with an indices size 1 and a data size 2, it will crash.
import tensorflow as tf
# indices = 1*[tf.random.uniform([1,2], dtype=tf.dtypes.int32, maxval=100)]
indices = [tf.constant([[0, 1]]),]
# data = 2*[tf.random.uniform([1,2], dtype=tf.dtypes.float32, maxval=100)]
data = [tf.constant([[5, 6]]), tf.constant([[7, 8]])]
tf.raw_ops.DynamicStitch(
indices=indices,
data=data)
Patches
We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629.
The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 as this is also affected.
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 Zizhuang Deng of IIE, UCAS
The vulnerability can be exploited over the network without needing physical access. It is easy for an attacker to exploit this vulnerability. An attacker needs basic access or low-level privileges. The attacker needs the user to perform some action, like clicking a link. The impact is confined to the system where the vulnerability exists. There is a low impact on the confidentiality of the information. There is a low impact on the integrity of the data. There is a high impact on the availability of the system.
Exploitation attempts have been detected. Elevated vigilance and prompt remediation are advised.
The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.
We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.
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