GHSA-rrx2-r989-2c43

Source
https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2022/02/GHSA-rrx2-r989-2c43/GHSA-rrx2-r989-2c43.json
Aliases
Published
2022-02-09T23:39:33Z
Modified
2022-09-19T02:32:02.364953Z
Details

Impact

The implementations of <code>Sparse*Cwise*</code> ops are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or CHECK-fails when building new TensorShape objects (so, assert failures based denial of service):

import tensorflow as tf
import numpy as np

tf.raw_ops.SparseDenseCwiseDiv(
    sp_indices=np.array([[9]]),
    sp_values=np.array([5]),
    sp_shape=np.array([92233720368., 92233720368]),
    dense=np.array([4]))

We are missing some validation on the shapes of the input tensors as well as directly constructing a large TensorShape with user-provided dimensions. The latter is an instance of TFSA-2021-198 (CVE-2021-41197) and is easily fixed by replacing a call to TensorShape constructor with a call to BuildTensorShape static helper factory.

Patches

We have patched the issue in GitHub commits 1b54cadd19391b60b6fcccd8d076426f7221d5e8 and e952a89b7026b98fe8cbe626514a93ed68b7c510.

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.

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 Faysal Hossain Shezan from University of Virginia.

References

Affected packages

PyPI / tensorflow

tensorflow

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0
Fixed
2.5.3

Affected versions

0.*

0.12.0
0.12.1

1.*

1.0.0
1.0.1
1.1.0
1.10.0
1.10.1
1.11.0
1.12.0
1.12.2
1.12.3
1.13.1
1.13.2
1.14.0
1.15.0
1.15.2
1.15.3
1.15.4
1.15.5
1.2.0
1.2.1
1.3.0
1.4.0
1.4.1
1.5.0
1.5.1
1.6.0
1.7.0
1.7.1
1.8.0
1.9.0

2.*

2.0.0
2.0.1
2.0.2
2.0.3
2.0.4
2.1.0
2.1.1
2.1.2
2.1.3
2.1.4
2.2.0
2.2.1
2.2.2
2.2.3
2.3.0
2.3.1
2.3.2
2.3.3
2.3.4
2.4.0
2.4.1
2.4.2
2.4.3
2.4.4
2.5.0
2.5.1
2.5.2

PyPI / tensorflow

tensorflow

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.6.0
Fixed
2.6.3

Affected versions

2.*

2.6.0
2.6.1
2.6.2

PyPI / tensorflow

tensorflow

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.7.0
Fixed
2.7.1

Affected versions

2.*

2.7.0

PyPI / tensorflow-cpu

tensorflow-cpu

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0
Fixed
2.5.3

Affected versions

1.*

1.15.0

2.*

2.1.0
2.1.1
2.1.2
2.1.3
2.1.4
2.2.0
2.2.1
2.2.2
2.2.3
2.3.0
2.3.1
2.3.2
2.3.3
2.3.4
2.4.0
2.4.1
2.4.2
2.4.3
2.4.4
2.5.0
2.5.1
2.5.2

PyPI / tensorflow-cpu

tensorflow-cpu

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.6.0
Fixed
2.6.3

Affected versions

2.*

2.6.0
2.6.1
2.6.2

PyPI / tensorflow-cpu

tensorflow-cpu

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.7.0
Fixed
2.7.1

Affected versions

2.*

2.7.0

PyPI / tensorflow-gpu

tensorflow-gpu

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0
Fixed
2.5.3

Affected versions

0.*

0.12.0
0.12.1

1.*

1.0.0
1.0.1
1.1.0
1.10.0
1.10.1
1.11.0
1.12.0
1.12.2
1.12.3
1.13.1
1.13.2
1.14.0
1.15.0
1.15.2
1.15.3
1.15.4
1.15.5
1.2.0
1.2.1
1.3.0
1.4.0
1.4.1
1.5.0
1.5.1
1.6.0
1.7.0
1.7.1
1.8.0
1.9.0

2.*

2.0.0
2.0.1
2.0.2
2.0.3
2.0.4
2.1.0
2.1.1
2.1.2
2.1.3
2.1.4
2.2.0
2.2.1
2.2.2
2.2.3
2.3.0
2.3.1
2.3.2
2.3.3
2.3.4
2.4.0
2.4.1
2.4.2
2.4.3
2.4.4
2.5.0
2.5.1
2.5.2

PyPI / tensorflow-gpu

tensorflow-gpu

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.6.0
Fixed
2.6.3

Affected versions

2.*

2.6.0
2.6.1
2.6.2

PyPI / tensorflow-gpu

tensorflow-gpu

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.7.0
Fixed
2.7.1

Affected versions

2.*

2.7.0