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GHSA-rmg2-f698-wq35
No affected components available
Impact
If ThreadUnsafeUnigramCandidateSampler is given input filterbank_channel_count greater than the allowed max size, TensorFlow will crash.
import tensorflow as tf
tf.raw_ops.Mfcc(
spectrogram = [[[1.38, 6.32, 5.75, 9.51]]],
sample_rate = 2,
upper_frequency_limit = 5.0,
lower_frequency_limit = 1.0,
filterbank_channel_count = 2**31 - 1,
dct_coefficient_count = 1
)
Patches
We have patched the issue in GitHub commit 39ec7eaf1428e90c37787e5b3fbd68ebd3c48860.
The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, 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 Vul AI.
The vulnerability can be exploited over the network without needing physical access. It is difficult for an attacker to exploit this vulnerability and may require special conditions. 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 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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