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GHSA-w74j-v8xh-3w5h
No affected components available
Impact
An attacker can cause undefined behavior via binding a reference to null pointer in tf.raw_ops.UnicodeEncode:
import tensorflow as tf
from tensorflow.python.ops import gen_string_ops
gen_string_ops.unicode_encode(
input_values=[],
input_splits=[],
output_encoding='UTF-8',
errors='ignore',
replacement_char='a')
The implementation reads the first dimension of the input_splits tensor before validating that this tensor is not empty:
const Tensor& input_splits = context->input(1);
const auto input_splits_flat = input_splits.flat<SPLITS_TYPE>();
TensorShape output_shape({input_splits.dim_size(0) - 1});
Patches
We have patched the issue in GitHub commit 2e0ee46f1a47675152d3d865797a18358881d7a6.
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 high impact on the integrity of the data. There is a high impact on the availability of the system.
Exploitation activity has been observed. Apply available patches or mitigations urgently.
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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