GHSA-gf2j-f278-xh4v

Suggest an improvement
Source
https://github.com/advisories/GHSA-gf2j-f278-xh4v
Import Source
https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2022/02/GHSA-gf2j-f278-xh4v/GHSA-gf2j-f278-xh4v.json
JSON Data
https://api.osv.dev/v1/vulns/GHSA-gf2j-f278-xh4v
Aliases
Published
2022-02-09T23:47:57Z
Modified
2024-11-13T22:47:26.631486Z
Severity
  • 6.5 (Medium) CVSS_V3 - CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H CVSS Calculator
  • 7.1 (High) CVSS_V4 - CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N CVSS Calculator
Summary
Division by zero in TFLite
Details

Impact

An attacker can craft a TFLite model that would trigger a division by zero in BiasAndClamp implementation:

inline void BiasAndClamp(float clamp_min, float clamp_max, int bias_size,
                         const float* bias_data, int array_size,
                         float* array_data) {
  // ...
  TFLITE_DCHECK_EQ((array_size % bias_size), 0);
  // ...
} 

There is no check that the bias_size is non zero.

Patches

We have patched the issue in GitHub commit 8c6f391a2282684a25cbfec7687bd5d35261a209.

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 Wang Xuan of Qihoo 360 AIVul Team.

References

Affected packages

PyPI / tensorflow

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Fixed
2.5.3

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
2.4.4
2.5.0
2.5.1
2.5.2

PyPI / tensorflow

Package

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

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.7.0
Fixed
2.7.1

Affected versions

2.*

2.7.0

PyPI / tensorflow-cpu

Package

Affected ranges

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

Package

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

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.7.0
Fixed
2.7.1

Affected versions

2.*

2.7.0

PyPI / tensorflow-gpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Fixed
2.5.3

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
2.4.4
2.5.0
2.5.1
2.5.2

PyPI / tensorflow-gpu

Package

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

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.7.0
Fixed
2.7.1

Affected versions

2.*

2.7.0