GHSA-374m-jm66-3vj8

Suggest an improvement
Source
https://github.com/advisories/GHSA-374m-jm66-3vj8
Import Source
https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/11/GHSA-374m-jm66-3vj8/GHSA-374m-jm66-3vj8.json
JSON Data
https://api.osv.dev/v1/vulns/GHSA-374m-jm66-3vj8
Aliases
Published
2021-11-10T18:41:47Z
Modified
2023-12-06T01:01:35.310511Z
Severity
  • 7.1 (High) CVSS_V3 - CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H CVSS Calculator
Summary
Heap OOB in `SparseBinCount`
Details

Impact

The implementation of SparseBinCount is vulnerable to a heap OOB:

import tensorflow as tf


tf.raw_ops.SparseBincount(
  indices=[[0],[1],[2]]
  values=[0,-10000000]
  dense_shape=[1,1]
  size=[1]
  weights=[3,2,1]
  binary_output=False)

This is because of missing validation between the elements of the values argument and the shape of the sparse output:

for (int64_t i = 0; i < indices_mat.dimension(0); ++i) {
  const int64_t batch = indices_mat(i, 0);
  const Tidx bin = values(i);
  ...
  out(batch, bin) = ...;
}

Patches

We have patched the issue in GitHub commit f410212e373eb2aec4c9e60bf3702eba99a38aba.

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.

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.

References

Affected packages

PyPI / tensorflow

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.6.0
Fixed
2.6.1

Affected versions

2.*

2.6.0

PyPI / tensorflow

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.5.0
Fixed
2.5.2

Affected versions

2.*

2.5.0
2.5.1

PyPI / tensorflow

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Fixed
2.4.4

Affected versions

0.*

0.12.0
0.12.1

1.*

1.0.0
1.0.1
1.1.0
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
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

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

PyPI / tensorflow-cpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.6.0
Fixed
2.6.1

Affected versions

2.*

2.6.0

PyPI / tensorflow-cpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.5.0
Fixed
2.5.2

Affected versions

2.*

2.5.0
2.5.1

PyPI / tensorflow-cpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Fixed
2.4.4

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

PyPI / tensorflow-gpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.6.0
Fixed
2.6.1

Affected versions

2.*

2.6.0

PyPI / tensorflow-gpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.5.0
Fixed
2.5.2

Affected versions

2.*

2.5.0
2.5.1

PyPI / tensorflow-gpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Fixed
2.4.4

Affected versions

0.*

0.12.0
0.12.1

1.*

1.0.0
1.0.1
1.1.0
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
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

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