| Package | Affected versions | Patched versions |
|---|---|---|
| tensorflow | ≥ 2.5.0, < 2.5.2≥ 2.6.0, < 2.6.1≥ 2.7.0rc0, < 2.7.0< 2.4.4 | 2.5.22.6.12.7.02.4.4 |
| tensorflow-cpu | ≥ 2.5.0, < 2.5.2≥ 2.6.0, < 2.6.1≥ 2.7.0rc0, < 2.7.0< 2.4.4 | 2.5.22.6.12.7.02.4.4 |
| tensorflow-gpu | ≥ 2.5.0, < 2.5.2≥ 2.6.0, < 2.6.1≥ 2.7.0rc0, < 2.7.0< 2.4.4 | 2.5.22.6.12.7.02.4.4 |
| tensorflow | = 2.7.0≥ 2.4.0, < 2.4.4≥ 2.5.0, < 2.5.2≥ 2.6.0, < 2.6.1 | 2.4.42.5.22.6.1 |
The ImmutableConst operation in TensorFlow can be tricked into reading arbitrary memory contents:
import tensorflow as tf
with open('/tmp/test','wb') as f:
f.write(b'\xe2'*128)
data = tf.raw_ops.ImmutableConst(dtype=tf.string,shape=3,memory_region_name='/tmp/test')
print(data)
This is because the tstring TensorFlow string class has a special case for memory mapped strings but the operation itself does not offer any support for this datatype.
We have patched the issue in GitHub commit 3712a2d3455e6ccb924daa5724a3652a86f6b585 and GitHub commit 1cb6bb6c2a6019417c9adaf9e6843ba75ee2580b.
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 members of the Aivul Team from Qihoo 360.
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