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GHSA-9c78-vcq7-7vxq

Out of bounds write in TFLite

Source: GitHub Advisory Database (reviewed) High CVE-2022-23561

Packages

EcosystemPackageAffectedFixed in
PyPI tensorflow < 2.5.3 2.5.3
PyPI tensorflow >= 2.6.0, < 2.6.3 2.6.3
PyPI tensorflow >= 2.7.0, < 2.7.1 2.7.1
PyPI tensorflow-cpu < 2.5.3 2.5.3
PyPI tensorflow-cpu >= 2.6.0, < 2.6.3 2.6.3
PyPI tensorflow-cpu >= 2.7.0, < 2.7.1 2.7.1
PyPI tensorflow-gpu < 2.5.3 2.5.3
PyPI tensorflow-gpu >= 2.6.0, < 2.6.3 2.6.3
PyPI tensorflow-gpu >= 2.7.0, < 2.7.1 2.7.1

Details

As written in the advisory (Markdown source, shown as plain text).

### Impact An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. ### Patches We have patched the issue in GitHub commit [6c0b2b70eeee588591680f5b7d5d38175fd7cdf6](https://github.com/tensorflow/tensorflow/commit/6c0b2b70eeee588591680f5b7d5d38175fd7cdf6). 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](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) 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

External links from the advisory. They lead to third-party sites.