EUVD-2026-21970

A vulnerability in the TFSMLayer class of the keras package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of .keras models, even when safemode=True. This bypasses the security guarantees of safemode and enables arbitrary attacker-controlled...

GHSA-4F3F-G24H-FR8M Keras has an untrusted deserialization vulnerability

A vulnerability in the TFSMLayer class of the keras package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of .keras models, even when safemode=True. This bypasses the security guarantees of safemode and enables arbitrary attacker-controlled...

DEBIAN-CVE-2026-1462

A vulnerability in the TFSMLayer class of the keras package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of .keras models, even when safemode=True. This bypasses the security guarantees of safemode and enables arbitrary attacker-controlled...

UBUNTU-CVE-2026-1462

A vulnerability in the TFSMLayer class of the keras package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of .keras models, even when safemode=True. This bypasses the security guarantees of safemode and enables arbitrary attacker-controlled...

CVE-2026-1462 Safe Mode Bypass in keras-team/keras

A vulnerability in the TFSMLayer class of the keras package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of .keras models, even when safemode=True. This bypasses the security guarantees of safemode and enables arbitrary attacker-controlled...

CVE-2026-1462

A vulnerability in the TFSMLayer class of the keras package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of .keras models, even when safemode=True. This bypasses the security guarantees of safemode and enables arbitrary attacker-controlled...

CVE-2026-1462

A vulnerability in the TFSMLayer class of the keras package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of .keras models, even when safemode=True. This bypasses the security guarantees of safemode and enables arbitrary attacker-controlled...

PT-2026-32367

A vulnerability in the TFSMLayer class of the keras package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of .keras models, even when safe mode=True. This bypasses the security guarantees of safe mode and enables arbitrary attacker-controll...

Keras 代码问题漏洞

Keras is an open-source deep learning framework with multiple backends. Version 3.13.0 of Keras contains a code vulnerability that stems from the TFSLayer class’s unconditional loading of external SavedModels, which may lead to arbitrary code execution...

TFSMLayer bypasses `safe_mode=True`, allowing attacker-controlled code execution during model inference

Summary TFSMLayer allows loading attacker-controlled TensorFlow SavedModels when deserializing a .keras model, even when safemode=True the default. While TensorFlow does not execute SavedModel functions during load, the attacker-controlled graph is registered during deserialization and executes...

BIT-TENSORFLOW-2020-15211 Out of bounds access in tensorflow-lite

In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indice...

BIT-TENSORFLOW-2020-5215 Segmentation faultin TensorFlow when converting a Python string to tf.float16

In TensorFlow before 1.15.2 and 2.0.1, converting a string from Python to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker c...

SUSE CVE-2020-26266

In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen...

PYSEC-2020-332

In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen...

PYSEC-2020-297

In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen...

PYSEC-2020-297

In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen...

PYSEC-2020-254

In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen...

PYSEC-2020-254

In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen...

PYSEC-2020-337

In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node given by outputindex and the input slot of the dst node...

CVE-2020-26266

In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen...