https://vulnerability.circl.lu Contains only the most 10 recent entries. http://www.rssboard.org/rss-specification python-feedgen en Tue, 29 Sep 2026 21:10:10 +0000 https://vulnerability.circl.lu/vuln/cve-2022-23594 <p><strong>Affected:</strong> tensorflow</p> <p>Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.</p> <p><strong>Affected:</strong> tensorflow</p> <p>Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.</p> https://vulnerability.circl.lu/vuln/cve-2022-23594 https://vulnerability.circl.lu/vuln/ghsa-9x52-887g-fhc2 <p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p> <p>### Impact The [TFG dialect of TensorFlow (MLIR)](https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/core/ir/importexport) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect.</p> <p>If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered. ### Patches We have patched the issue in multiple GitHub commits and these will be included in TensorFlow 2.8.0 and TensorFlow 2.7.1, as both are affected. ### 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.</p> <p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p> <p>### Impact The [TFG dialect of TensorFlow (MLIR)](https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/core/ir/importexport) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect.</p> <p>If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered. ### Patches We have patched the issue in multiple GitHub commits and these will be included in TensorFlow 2.8.0 and TensorFlow 2.7.1, as both are affected. ### 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.</p> https://vulnerability.circl.lu/vuln/ghsa-9x52-887g-fhc2