PYSEC-2026-3227 TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`

Impact The implementation of Conv2DBackpropInput requires inputsizes to be 4-dimensional. Otherwise, it gives a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf strides = 1, 1, 1, 1 padding = "SAME" usecudnnongpu = True explicitpaddings =...

PYSEC-2026-3101 TensorFlow vulnerable to segfault in `QuantizedBiasAdd`

Impact If QuantizedBiasAdd is given mininput, maxinput, minbias, maxbias tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outtype = tf.qint32 input = tf.constant85,170,255, shape=3, dtype=tf.quint8 bias =...

PYSEC-2026-3305 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`

Impact If FakeQuantWithMinMaxVars is given min or max tensors of a nonzero rank, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf numbits = 8 narrowrange = False inputs = tf.constant0, shape=2,3, dtype=tf.float32 min = tf.constant0,...

PYSEC-2026-3326 TensorFlow vulnerable to segfault in `QuantizedInstanceNorm`

Impact If QuantizedInstanceNorm is given xmin or xmax tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outputrangegiven = False givenymin = 0 givenymax = 0 varianceepsilon = 1e-05 minseparation = 0.001 x =...

PYSEC-2026-3272 TensorFlow vulnerable to segfault in `QuantizedBiasAdd`

Impact If QuantizedBiasAdd is given mininput, maxinput, minbias, maxbias tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outtype = tf.qint32 input = tf.constant85,170,255, shape=3, dtype=tf.quint8 bias =...

PYSEC-2026-3183 TensorFlow vulnerable to segfault in `QuantizedInstanceNorm`

Impact If QuantizedInstanceNorm is given xmin or xmax tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outputrangegiven = False givenymin = 0 givenymax = 0 varianceepsilon = 1e-05 minseparation = 0.001 x =...

PYSEC-2026-3263 TensorFlow vulnerable to `CHECK` fail in `AvgPoolGrad`

Impact The implementation of AvgPoolGrad does not fully validate the input originputshape. This results in a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf ksize = 1, 2, 2, 1 strides = 1, 2, 2, 1 padding = "VALID" dataformat = "NHWC"...

PYSEC-2026-3273 TensorFlow vulnerable to segfault in `QuantizedAvgPool`

Impact If QuantizedAvgPool is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf ksize = 1, 2, 2, 1 strides = 1, 2, 2, 1 padding = "SAME" input = tf.constant1, shape=1,4,4,2,...

PYSEC-2026-3338 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`

Impact When tf.quantization.fakequantwithminmaxvarsperchannelgradient receives input min or max of rank other than 1, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=1,1, dtype=tf.float32, maxval=None...

PYSEC-2026-3083 TensorFlow vulnerable to `CHECK` fail in `AvgPoolGrad`

Impact The implementation of AvgPoolGrad does not fully validate the input originputshape. This results in a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf ksize = 1, 2, 2, 1 strides = 1, 2, 2, 1 padding = "VALID" dataformat = "NHWC"...

PYSEC-2026-3244 TensorFlow vulnerable to segfault in `QuantizedAdd`

Impact If QuantizedAdd is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf Toutput = tf.qint32 x = tf.constant140, shape=1, dtype=tf.quint8 y = tf.constant26, shape=10,...

PYSEC-2026-3374 TensorFlow vulnerable to `CHECK` fail in `TensorListScatter` and `TensorListScatterV2`

Impact When TensorListScatter and TensorListScatterV2 receive an elementshape of a rank greater than one, they give a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=2, 2, 2, dtype=tf.float16, maxval=None...

PYSEC-2026-3371 TensorFlow vulnerable to segfault in `QuantizedAdd`

Impact If QuantizedAdd is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf Toutput = tf.qint32 x = tf.constant140, shape=1, dtype=tf.quint8 y = tf.constant26, shape=10,...

PYSEC-2026-3103 TensorFlow vulnerable to segfault in `QuantizedAvgPool`

Impact If QuantizedAvgPool is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf ksize = 1, 2, 2, 1 strides = 1, 2, 2, 1 padding = "SAME" input = tf.constant1, shape=1,4,4,2,...

PYSEC-2026-3199 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`

Impact When tf.quantization.fakequantwithminmaxvarsperchannelgradient receives input min or max of rank other than 1, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=1,1, dtype=tf.float32, maxval=None...

PYSEC-2026-3378 TensorFlow vulnerable to `CHECK` fail in `SetSize`

Impact When SetSize receives an input setshape that is not a 1D tensor, it gives a CHECK fails that can be used to trigger a denial of service attack. python import tensorflow as tf arg0=1 arg1=1,1 arg2=1 arg3=True arg4='' tf.rawops.SetSizesetindices=arg0, setvalues=arg1, setshape=arg2,...

PYSEC-2026-3318 TensorFlow vulnerable to segfault in `BlockLSTMGradV2`

Impact The implementation of BlockLSTMGradV2 does not fully validate its inputs. - wci, wcf, wco, b must be rank 1 - w, csprev, hprev must be rank 2 - x must be rank 3 This results in a a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf usepeephole =...

PYSEC-2026-3255 TensorFlow vulnerable to `CHECK` fail in `SetSize`

Impact When SetSize receives an input setshape that is not a 1D tensor, it gives a CHECK fails that can be used to trigger a denial of service attack. python import tensorflow as tf arg0=1 arg1=1,1 arg2=1 arg3=True arg4='' tf.rawops.SetSizesetindices=arg0, setvalues=arg1, setshape=arg2,...

PYSEC-2026-3307 TensorFlow vulnerable to `CHECK` fail in `TensorListFromTensor`

Impact When TensorListFromTensor receives an elementshape of a rank greater than one, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=6, 6, 2, dtype=tf.bfloat16, maxval=None arg1=tf.random.uniformshape=6, 9, 1, 3,...

PYSEC-2026-3170 TensorFlow vulnerable to segfault in `BlockLSTMGradV2`

Impact The implementation of BlockLSTMGradV2 does not fully validate its inputs. - wci, wcf, wco, b must be rank 1 - w, csprev, hprev must be rank 2 - x must be rank 3 This results in a a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf usepeephole =...

PYSEC-2026-3233 TensorFlow vulnerable to segfault in `LowerBound` and `UpperBound`

Impact If LowerBound or UpperBound is given an emptysortedinputs input, it results in a nullptr dereference, leading to a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outtype = tf.int32 sortedinputs = tf.constant, shape=10,0, dtype=tf.float32...

PYSEC-2026-3363 TensorFlow vulnerable to segfault in `LowerBound` and `UpperBound`

Impact If LowerBound or UpperBound is given an emptysortedinputs input, it results in a nullptr dereference, leading to a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outtype = tf.int32 sortedinputs = tf.constant, shape=10,0, dtype=tf.float32...

PYSEC-2026-3248 TensorFlow vulnerable to `CHECK` fail in `TensorListScatter` and `TensorListScatterV2`

Impact When TensorListScatter and TensorListScatterV2 receive an elementshape of a rank greater than one, they give a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=2, 2, 2, dtype=tf.float16, maxval=None...

PYSEC-2026-3155 TensorFlow vulnerable to `CHECK` fail in `TensorListFromTensor`

Impact When TensorListFromTensor receives an elementshape of a rank greater than one, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=6, 6, 2, dtype=tf.bfloat16, maxval=None arg1=tf.random.uniformshape=6, 9, 1, 3,...

PYSEC-2026-3370 TensorFlow vulnerable to `CHECK` failure in `TensorListReserve` via missing validation

Impact In core/kernels/listkernels.cc's TensorListReserve, numelements is assumed to be a tensor of size 1. When a numelements of more than 1 element is provided, then tf.rawops.TensorListReserve fails the CHECKEQ in CheckIsAlignedAndSingleElement. python import tensorflow as tf...

PYSEC-2026-3337 TensorFlow vulnerable to `CHECK` failures in `UnbatchGradOp`

Impact The UnbatchGradOp function takes an argument id that is assumed to be a scalar. A nonscalar id can trigger a CHECK failure and crash the program. python import numpy as np import tensorflow as tf id is not scalar tf.rawops.UnbatchGradoriginalinput= tf.constant1,batchindex=tf.constant0,0,0 ...

PYSEC-2026-3133 TensorFlow vulnerable to `CHECK` failures in `FractionalAvgPoolGrad`

Impact The implementation of FractionalAvgPoolGrad does not fully validate the input originputtensorshape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack. python import tensorflow as tf overlapping = True originputtensorshape =...

PYSEC-2026-3198 TensorFlow vulnerable to `CHECK` failures in `UnbatchGradOp`

Impact The UnbatchGradOp function takes an argument id that is assumed to be a scalar. A nonscalar id can trigger a CHECK failure and crash the program. python import numpy as np import tensorflow as tf id is not scalar tf.rawops.UnbatchGradoriginalinput= tf.constant1,batchindex=tf.constant0,0,0 ...

PYSEC-2026-3381 TensorFlow vulnerable to Int overflow in `RaggedRangeOp`

Impact The RaggedRangOp function takes an argument limits that is eventually used to construct a TensorShape as an int64. If limits is a very large float, it can overflow when converted to an int64. This triggers an InvalidArgument but also throws an abort signal that crashes the program. python...

PYSEC-2026-3296 TensorFlow vulnerable to `CHECK` failures in `FractionalAvgPoolGrad`

Impact The implementation of FractionalAvgPoolGrad does not fully validate the input originputtensorshape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack. python import tensorflow as tf overlapping = True originputtensorshape =...

PYSEC-2026-3172 TensorFlow vulnerable to `CHECK` fail in `CollectiveGather`

Impact When CollectiveGather receives an scalar input input, it gives a CHECK fails that can be used to trigger a denial of service attack. python import tensorflow as tf arg0=1 arg1=1 arg2=1 arg3=1 arg4=3, 3,3 arg5='auto' arg6=0 arg7='' tf.rawops.CollectiveGatherinput=arg0, groupsize=arg1,...

PYSEC-2026-3320 TensorFlow vulnerable to `CHECK` fail in `CollectiveGather`

Impact When CollectiveGather receives an scalar input input, it gives a CHECK fails that can be used to trigger a denial of service attack. python import tensorflow as tf arg0=1 arg1=1 arg2=1 arg3=1 arg4=3, 3,3 arg5='auto' arg6=0 arg7='' tf.rawops.CollectiveGatherinput=arg0, groupsize=arg1,...

PYSEC-2026-3259 TensorFlow vulnerable to Int overflow in `RaggedRangeOp`

Impact The RaggedRangOp function takes an argument limits that is eventually used to construct a TensorShape as an int64. If limits is a very large float, it can overflow when converted to an int64. This triggers an InvalidArgument but also throws an abort signal that crashes the program. python...

PYSEC-2026-3346 TensorFlow vulnerable to `CHECK` fail in `DrawBoundingBoxes`

Impact When DrawBoundingBoxes receives an input boxes that is not of dtype float, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf import numpy as np arg0=tf.constantvalue=np.random.randomsize=1, 3, 2, 3, shape=1, 3, 2, 3, dtype=tf.half...

PYSEC-2026-3243 TensorFlow vulnerable to `CHECK` failure in `TensorListReserve` via missing validation

Impact In core/kernels/listkernels.cc's TensorListReserve, numelements is assumed to be a tensor of size 1. When a numelements of more than 1 element is provided, then tf.rawops.TensorListReserve fails the CHECKEQ in CheckIsAlignedAndSingleElement. python import tensorflow as tf...

PYSEC-2026-3380 TensorFlow vulnerable to `CHECK` failures in `AvgPool3DGrad`

Impact The implementation of AvgPool3DGradOp does not fully validate the input originputshape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf ksize = 1, 1, 1, 1, 1 strides = 1, 1, 1, 1, 1 padding ...

PYSEC-2026-3209 TensorFlow vulnerable to `CHECK` fail in `DrawBoundingBoxes`

Impact When DrawBoundingBoxes receives an input boxes that is not of dtype float, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf import numpy as np arg0=tf.constantvalue=np.random.randomsize=1, 3, 2, 3, shape=1, 3, 2, 3, dtype=tf.half...

PYSEC-2026-3228 TensorFlow vulnerable to floating point exception in `Conv2D`

Impact If Conv2D is given empty input and the filter and padding sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np with tf.device"CPU": also can...

PYSEC-2026-3257 TensorFlow vulnerable to `CHECK` failures in `AvgPool3DGrad`

Impact The implementation of AvgPool3DGradOp does not fully validate the input originputshape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf ksize = 1, 1, 1, 1, 1 strides = 1, 1, 1, 1, 1 padding ...

PYSEC-2026-3361 TensorFlow vulnerable to floating point exception in `Conv2D`

Impact If Conv2D is given empty input and the filter and padding sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np with tf.device"CPU": also can...

PYSEC-2026-3177 TensorFlow vulnerable to null dereference on MLIR on empty function attributes

Impact Eig can be fed an incorrect Tout input, resulting in a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf import numpy as np arg0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2, dtype=tf.float32 arg1=tf.complex128 arg2=True arg3=''...

PYSEC-2026-3322 TensorFlow vulnerable to null dereference on MLIR on empty function attributes

Impact Eig can be fed an incorrect Tout input, resulting in a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf import numpy as np arg0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2, dtype=tf.float32 arg1=tf.complex128 arg2=True arg3=''...

PYSEC-2026-3256 TensorFlow vulnerable to segfault in `Requantize`

Impact If Requantize is given inputmin, inputmax, requestedoutputmin, requestedoutputmax tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outtype = tf.quint8 input = tf.constant1, shape=3, dtype=tf.qint32...

PYSEC-2026-3216 TensorFlow vulnerable to `CHECK` fail in `Unbatch`

Impact When Unbatch receives a nonscalar input id, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf import numpy as np arg0=tf.constantvalue=np.random.randomsize=3, 3, 1, dtype=tf.float64 arg1=tf.constantvalue=np.random.randint0,100,size=3, 3, 1,...

PYSEC-2026-3352 TensorFlow vulnerable to `CHECK` fail in `Unbatch`

Impact When Unbatch receives a nonscalar input id, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf import numpy as np arg0=tf.constantvalue=np.random.randomsize=3, 3, 1, dtype=tf.float64 arg1=tf.constantvalue=np.random.randint0,100,size=3, 3, 1,...

PYSEC-2026-3379 TensorFlow vulnerable to segfault in `Requantize`

Impact If Requantize is given inputmin, inputmax, requestedoutputmin, requestedoutputmax tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outtype = tf.quint8 input = tf.constant1, shape=3, dtype=tf.qint32...

PYSEC-2026-3325 TensorFlow vulnerable to null dereference on MLIR on empty function attributes

Impact When mlir::tfg::ConvertGenericFunctionToFunctionDef is given empty function attributes, it gives a null dereference. cpp // Import the function attributes with a tf. prefix to match the current // infrastructure expectations. for const auto& namedAttr : func.attr const std::string& name =...

PYSEC-2026-3295 TensorFlow vulnerable to null-dereference in `mlir::tfg::GraphDefImporter::ConvertNodeDef`

Impact When mlir::tfg::GraphDefImporter::ConvertNodeDef tries to convert NodeDefs without an op name, it crashes. cpp Status GraphDefImporter::ConvertNodeDefOpBuilder &builder, ConversionState &s, const NodeDef &node VLOG4 opdef; else auto it = functionopdefs.findnode.op; if it ==...

PYSEC-2026-3132 TensorFlow vulnerable to null-dereference in `mlir::tfg::GraphDefImporter::ConvertNodeDef`

Impact When mlir::tfg::GraphDefImporter::ConvertNodeDef tries to convert NodeDefs without an op name, it crashes. cpp Status GraphDefImporter::ConvertNodeDefOpBuilder &builder, ConversionState &s, const NodeDef &node VLOG4 opdef; else auto it = functionopdefs.findnode.op; if it ==...

PYSEC-2026-3180 TensorFlow vulnerable to null dereference on MLIR on empty function attributes

Impact When mlir::tfg::ConvertGenericFunctionToFunctionDef is given empty function attributes, it gives a null dereference. cpp // Import the function attributes with a tf. prefix to match the current // infrastructure expectations. for const auto& namedAttr : func.attr const std::string& name =...