GHSA-j8qh-3xrq-c825

Suggest an improvement
Source
https://github.com/advisories/GHSA-j8qh-3xrq-c825
Import Source
https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/05/GHSA-j8qh-3xrq-c825/GHSA-j8qh-3xrq-c825.json
JSON Data
https://api.osv.dev/v1/vulns/GHSA-j8qh-3xrq-c825
Aliases
Published
2021-05-21T14:28:04Z
Modified
2024-08-29T21:31:07.428581Z
Severity
  • 2.5 (Low) CVSS_V3 - CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L CVSS Calculator
  • 2.0 (Low) CVSS_V4 - CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N CVSS Calculator
Summary
Division by zero in TFLite's implementation of `OneHot`
Details

Impact

The implementation of the OneHot TFLite operator is vulnerable to a division by zero error:

int prefix_dim_size = 1;
for (int i = 0; i < op_context.axis; ++i) {
  prefix_dim_size *= op_context.indices->dims->data[i];
}
const int suffix_dim_size = NumElements(op_context.indices) / prefix_dim_size;

An attacker can craft a model such that at least one of the dimensions of indices would be 0. In turn, the prefix_dim_size value would become 0.

Patches

We have patched the issue in GitHub commit 3ebedd7e345453d68e279cfc3e4072648e5e12e5.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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
2.1.4

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

PyPI / tensorflow

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.2.0
Fixed
2.2.3

Affected versions

2.*

2.2.0
2.2.1
2.2.2

PyPI / tensorflow

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.3.0
Fixed
2.3.3

Affected versions

2.*

2.3.0
2.3.1
2.3.2

PyPI / tensorflow

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.4.0
Fixed
2.4.2

Affected versions

2.*

2.4.0
2.4.1

PyPI / tensorflow-cpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Fixed
2.1.4

Affected versions

1.*

1.15.0

2.*

2.1.0
2.1.1
2.1.2
2.1.3

PyPI / tensorflow-cpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.2.0
Fixed
2.2.3

Affected versions

2.*

2.2.0
2.2.1
2.2.2

PyPI / tensorflow-cpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.3.0
Fixed
2.3.3

Affected versions

2.*

2.3.0
2.3.1
2.3.2

PyPI / tensorflow-cpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.4.0
Fixed
2.4.2

Affected versions

2.*

2.4.0
2.4.1

PyPI / tensorflow-gpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Fixed
2.1.4

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

PyPI / tensorflow-gpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.2.0
Fixed
2.2.3

Affected versions

2.*

2.2.0
2.2.1
2.2.2

PyPI / tensorflow-gpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.3.0
Fixed
2.3.3

Affected versions

2.*

2.3.0
2.3.1
2.3.2

PyPI / tensorflow-gpu

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
2.4.0
Fixed
2.4.2

Affected versions

2.*

2.4.0
2.4.1