Google TensorFlow Buffer Overflow Vulnerability (CNVD-2021-00094)

Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google USA. Google TensorFlow suffers from a buffer overflow vulnerability that stems from a tensor buffer being populated with the default value for the type, but forgetting to initialize the quantized...

Google TensorFlow Denial of Service Vulnerability (CNVD-2021-00093)

Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google USA. Google TensorFlow suffers from a denial-of-service vulnerability that stems from the LSTM GRU layer receiving a zero-length input when using a CUDA backend, which results in a check failure. An...

CVE-2020-26269

In TensorFlow release candidate versions 2.4.0rc, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel...

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...

CVE-2020-26270

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer...

CVE-2020-26269

In TensorFlow release candidate versions 2.4.0rc, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel...

CVE-2020-26267

In affected versions of TensorFlow the tf.rawops.DataFormatVecPermute API does not validate the srcformat and dstformat attributes. The code assumes that these two arguments define a permutation of NHWC. This can result in uninitialized memory accesses, read outside of bounds and even crashes. Th...

CVE-2020-26268

In affected versions of TensorFlow the tf.rawops.ImmutableConst operation returns a constant tensor created from a memory mapped file which is assumed immutable. However, if the type of the tensor is not an integral type, the operation crashes the Python interpreter as it tries to write to the...

CVE-2020-26267

In affected versions of TensorFlow the tf.rawops.DataFormatVecPermute API does not validate the srcformat and dstformat attributes. The code assumes that these two arguments define a permutation of NHWC. This can result in uninitialized memory accesses, read outside of bounds and even crashes. Th...

CVE-2020-26268

In affected versions of TensorFlow the tf.rawops.ImmutableConst operation returns a constant tensor created from a memory mapped file which is assumed immutable. However, if the type of the tensor is not an integral type, the operation crashes the Python interpreter as it tries to write to the...

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...

CVE-2020-26270

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer...

Design/Logic Flaw

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-2020-256

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer...

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-2020-299

In affected versions of TensorFlow the tf.rawops.ImmutableConst operation returns a constant tensor created from a memory mapped file which is assumed immutable. However, if the type of the tensor is not an integral type, the operation crashes the Python interpreter as it tries to write to the...

PYSEC-2020-334

In affected versions of TensorFlow the tf.rawops.ImmutableConst operation returns a constant tensor created from a memory mapped file which is assumed immutable. However, if the type of the tensor is not an integral type, the operation crashes the Python interpreter as it tries to write to the...

PYSEC-2020-300

In TensorFlow release candidate versions 2.4.0rc, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel...

PYSEC-2020-336

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer...