The implementation of StringNGrams
can be used to trigger a denial of service attack by causing an OOM condition after an integer overflow:
import tensorflow as tf
tf.raw_ops.StringNGrams(
data=['123456'],
data_splits=[0,1],
separator='a'*15,
ngram_widths=[],
left_pad='',
right_pad='',
pad_width=-5,
preserve_short_sequences=True)
We are missing a validation on pad_witdh
and that result in computing a negative value for ngram_width
which is later used to allocate parts of the output.
We have patched the issue in GitHub commit f68fdab93fb7f4ddb4eb438c8fe052753c9413e8.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
This vulnerability has been reported by Yu Tian of Qihoo 360 AIVul Team.
{ "nvd_published_at": "2022-02-03T12:15:00Z", "cwe_ids": [ "CWE-190", "CWE-400" ], "severity": "MODERATE", "github_reviewed": true, "github_reviewed_at": "2022-02-03T19:23:04Z" }