FlawAtlas
Search the atlas
CVE-2022-23572 Moderate

Crash when type cannot be specialized in Tensorflow

### Impact Under certain scenarios, TensorFlow can fail to specialize a type during [shape inference](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L168-L174): ```cc void InferenceContext::PreInputInit( const OpDef& op_def, const std::vector<const Tensor*>& input_tensors, const std::vector<ShapeHandle>& input_tensors_as_shapes) { const auto ret = full_type::SpecializeType(attrs_, op_def); DCHECK(ret.status().ok()) << "while instantiating types: " << ret.status(); ret_types_ = ret.ValueOrDie(); // ... } ``` However, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure. ### Patches We have patched the issue in GitHub commit [cb164786dc891ea11d3a900e90367c339305dc7b](https://github.com/tensorflow/tensorflow/commit/cb164786dc891ea11d3a900e90367c339305dc7b). The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, 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.

Exploit probability 1.0%
Published July 9, 2026
Required by Not available
Last source change July 13, 2026

02 / AFFECTED SOFTWARE

Affected packages

Bitnami tensorflow
PyPI tensorflow-cpu

26 explicit affected versions

PyPI tensorflow

62 explicit affected versions

PyPI tensorflow-cpu

27 explicit affected versions

PyPI tensorflow-gpu

62 explicit affected versions

PyPI tensorflow-gpu

61 explicit affected versions

PyPI tensorflow

62 explicit affected versions

Unknown Unknown

18 explicit affected versions

03 / CONNECTIONS

Connected vulnerabilities

04 / EVIDENCE

Source records

Open Source Vulnerabilities GHSA-rww7-2gpw-fv6j

### Impact Under certain scenarios, TensorFlow can fail to specialize a type during [shape inference](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L168-L174): ```cc void InferenceContext::PreInputInit( const OpDef& op_def, const std::vector<const Tensor*>& input_tensors, const std::vector<ShapeHandle>& input_tensors_as_shapes) { const auto ret = full_type::SpecializeType(attrs_, op_def); DCHECK(ret.status().ok()) << "while instantiating types: " << ret.status(); ret_types_ = ret.ValueOrDie(); // ... } ``` However, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure. ### Patches We have patched the issue in GitHub commit [cb164786dc891ea11d3a900e90367c339305dc7b](https://github.com/tensorflow/tensorflow/commit/cb164786dc891ea11d3a900e90367c339305dc7b). The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, 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.

View original source
Open Source Vulnerabilities PYSEC-2022-81

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, TensorFlow can fail to specialize a type during shape inference. This case is covered by the `DCHECK` function however, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.

View original source
Open Source Vulnerabilities BIT-tensorflow-2022-23572

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, TensorFlow can fail to specialize a type during shape inference. This case is covered by the `DCHECK` function however, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.

View original source
Open Source Vulnerabilities PYSEC-2026-3241

### Impact Under certain scenarios, TensorFlow can fail to specialize a type during [shape inference](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L168-L174): ```cc void InferenceContext::PreInputInit( const OpDef& op_def, const std::vector<const Tensor*>& input_tensors, const std::vector<ShapeHandle>& input_tensors_as_shapes) { const auto ret = full_type::SpecializeType(attrs_, op_def); DCHECK(ret.status().ok()) << "while instantiating types: " << ret.status(); ret_types_ = ret.ValueOrDie(); // ... } ``` However, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure. ### Patches We have patched the issue in GitHub commit [cb164786dc891ea11d3a900e90367c339305dc7b](https://github.com/tensorflow/tensorflow/commit/cb164786dc891ea11d3a900e90367c339305dc7b). The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, 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.

View original source
Open Source Vulnerabilities PYSEC-2022-136

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, TensorFlow can fail to specialize a type during shape inference. This case is covered by the `DCHECK` function however, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.

View original source
Open Source Vulnerabilities CVE-2022-23572

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, TensorFlow can fail to specialize a type during shape inference. This case is covered by the `DCHECK` function however, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.

View original source

05 / REFERENCES

Further evidence