PYSEC-2026-3088 Segfault and OOB write due to incomplete validation in `EditDistance` in TensorFlow

Impact The implementation of tf.rawops.EditDistance has incomplete validation. Users can pass negative values to cause a segmentation fault based denial of service: python import tensorflow as tf hypothesisindices = tf.constant-1250999896764, shape=3, 3, dtype=tf.int64 hypothesisvalues =...

PYSEC-2026-3167 Type confusion leading to `CHECK`-failure based denial of service in TensorFlow

Impact The macros that TensorFlow uses for writing assertions e.g., CHECKLT, CHECKGT, etc. have an incorrect logic when comparing sizet and int values. Due to type conversion rules, several of the macros would trigger incorrectly. Patches We have patched the issue in GitHub commit...

PYSEC-2026-3382 Segfault if `tf.histogram_fixed_width` is called with NaN values in TensorFlow

Impact The implementation of tf.histogramfixedwidth is vulnerable to a crash when the values array contain NaN elements: python import tensorflow as tf import numpy as np tf.histogramfixedwidthvalues=np.nan, valuerange=1,2 The implementation assumes that all floating point operations are defined...

Segfault and OOB write due to incomplete validation in `EditDistance` in TensorFlow

ImpactThe implementation of tf.rawops.EditDistance has incomplete validation. Users can pass negative values to cause a segmentation fault based denial of service:pythonimport tensorflow as tfhypothesisindices = tf.constant-1250999896764, shape=3, 3, dtype=tf.int64 hypothesisvalues = tf.constant0...

PYSEC-2026-3339 Heap buffer overflow due to incorrect hash function in TensorFlow

Impact The TensorKey hash function used total estimated AllocatedBytes, which a is an estimate per tensor, and b is a very poor hash function for constants e.g. int32t. It also tried to access individual tensor bytes through tensor.data of size AllocatedBytes. This led to ASAN failures because th...

PYSEC-2026-3112 Undefined behavior when users supply invalid resource handles

Impact Multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid: python import tensorflow as tf tf.rawops.QueueIsClosedV2handle= python import tensorflow as tf tf.summary.flushwriter= In graph mode, it would have been impossible to perform these...

PYSEC-2026-3266 Segfault and OOB write due to incomplete validation in `EditDistance` in TensorFlow

Impact The implementation of tf.rawops.EditDistance has incomplete validation. Users can pass negative values to cause a segmentation fault based denial of service: python import tensorflow as tf hypothesisindices = tf.constant-1250999896764, shape=3, 3, dtype=tf.int64 hypothesisvalues =...

PYSEC-2026-3315 Type confusion leading to `CHECK`-failure based denial of service in TensorFlow

Impact The macros that TensorFlow uses for writing assertions e.g., CHECKLT, CHECKGT, etc. have an incorrect logic when comparing sizet and int values. Due to type conversion rules, several of the macros would trigger incorrectly. Patches We have patched the issue in GitHub commit...

PYSEC-2026-3280 Undefined behavior when users supply invalid resource handles

Impact Multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid: python import tensorflow as tf tf.rawops.QueueIsClosedV2handle= python import tensorflow as tf tf.summary.flushwriter= In graph mode, it would have been impossible to perform these...

PYSEC-2026-3260 Segfault if `tf.histogram_fixed_width` is called with NaN values in TensorFlow

Impact The implementation of tf.histogramfixedwidth is vulnerable to a crash when the values array contain NaN elements: python import tensorflow as tf import numpy as np tf.histogramfixedwidthvalues=np.nan, valuerange=1,2 The implementation assumes that all floating point operations are defined...

Missing validation results in undefined behavior in `QuantizedConv2D`

ImpactThe implementation of tf.rawops.QuantizedConv2D does not fully validate the input arguments:pythonimport tensorflow as tfinput = tf.constant1, shape=1, 2, 3, 3, dtype=tf.quint8filter = tf.constant1, shape=1, 2, 3, 3, dtype=tf.quint8 bad argsmininput = tf.constant, shape=0,...

Segfault due to missing support for quantized types

ImpactThere is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1. ops which don't yet have support for quantized types added after migration to TF 2.x:pythonimport numpy as npimport tensorflow as...

Segfault due to missing support for quantized types

ImpactThere is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1. ops which don't yet have support for quantized types added after migration to TF 2.x:pythonimport numpy as npimport tensorflow as...

Missing validation results in undefined behavior in `SparseTensorDenseAdd

ImpactThe implementation of tf.rawops.SparseTensorDenseAdd does not fully validate the input arguments:pythonimport tensorflow as tfaindices = tf.constant0, shape=17, 2, dtype=tf.int64avalues = tf.constant, shape=0, dtype=tf.float32ashape = tf.constant6, 12, shape=2, dtype=tf.int64b =...

Integer overflow in `SpaceToBatchND`

ImpactThe implementation of tf.rawops.SpaceToBatchND in all backends such as XLA and handwritten kernels is vulnerable to an integer overflow:pythonimport tensorflow as tfinput = tf.constant-3.5e+35, shape=10,19,22, dtype=tf.float32blockshape = tf.constant-1879048192, shape=2,...

Integer overflow in `SpaceToBatchND`

ImpactThe implementation of tf.rawops.SpaceToBatchND in all backends such as XLA and handwritten kernels is vulnerable to an integer overflow:pythonimport tensorflow as tfinput = tf.constant-3.5e+35, shape=10,19,22, dtype=tf.float32blockshape = tf.constant-1879048192, shape=2,...

Denial of service in `tf.ragged.constant` due to lack of validation

ImpactThe implementation of tf.ragged.constant does not fully validate the input arguments. This results in a denial of service by consuming all available memory:pythonimport tensorflow as tftf.ragged.constantpylist=,raggedrank=8968073515812833920 PatchesWe have patched the issue in GitHub commit...

Denial of service in `tf.ragged.constant` due to lack of validation

ImpactThe implementation of tf.ragged.constant does not fully validate the input arguments. This results in a denial of service by consuming all available memory:pythonimport tensorflow as tftf.ragged.constantpylist=,raggedrank=8968073515812833920 PatchesWe have patched the issue in GitHub commit...

PYSEC-2026-3274 Segfault due to missing support for quantized types

Impact There is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1. ops which don't yet have support for quantized types added after migration to TF 2.x: python import numpy as np import tensorflow as tf...

PYSEC-2026-3342 Missing validation causes denial of service via `Conv3DBackpropFilterV2`

Impact The implementation of tf.rawops.UnsortedSegmentJoin does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack: python import tensorflow as tf tf.strings.unsortedsegmentjoin inputs='123', segmentids=0, numsegments=-1...