https://vulnerability.circl.lu/rss/recent/all/10 Most recent entries from all 2026-09-29T21:10:10.463733+00:00 Vulnerability-Lookup info@circl.lu python-feedgen Contains only the most 10 recent entries. https://vulnerability.circl.lu/vuln/cve-2022-23594 CVE-2022-23594 — Out of bounds read in Tensorflow 2026-09-29T21:10:10.571493+00:00

Affected: tensorflow

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.

 https://vulnerability.circl.lu/vuln/ghsa-9x52-887g-fhc2 GHSA-9x52-887g-fhc2 — Out of bounds read in Tensorflow 2026-09-29T21:10:10.571635+00:00

Affected: PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu

### 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.

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.