FPE in `tf.image.generate_bounding_box_proposals`

ImpactWhen running on GPU, tf.image.generateboundingboxproposals receives a scores input that must be of rank 4 but is not checked.pythonimport tensorflow as tfa = tf.constantvalue=1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0b =...

Overflow in `FusedResizeAndPadConv2D`

ImpactWhen tf.rawops.FusedResizeAndPadConv2D is given a large tensor shape, it overflows.pythonimport tensorflow as tfmode = "REFLECT"strides = 1, 1, 1, 1padding = "SAME"resizealigncorners = Falseinput = tf.constant147, shape=3,3,1,1, dtype=tf.float16size = tf.constant1879048192,1879048192,...

TensorFlow vulnerable to `CHECK` fail in `ParameterizedTruncatedNormal`

ImpactParameterizedTruncatedNormal assumes shape is of type int32. A valid shape of type int64 results in a mismatched type CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfseed = 1618seed2 = 0shape = tf.random.uniformshape=3, minval=-10000,...

TensorFlow vulnerable to `CHECK` fail in `tf.linalg.matrix_rank`

ImpactWhen tf.linalg.matrixrank receives an empty input a, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfa = tf.constant, shape=0, 1, 1, dtype=tf.float32tf.linalg.matrixranka=a PatchesWe have patched the issue in GitHub commi...

PYSEC-2026-3285 TensorFlow vulnerable to segfault in `QuantizedMatMul`

Impact If QuantizedMatMul is given nonscalar input for: - mina - maxa - minb - maxb It gives a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf Toutput = tf.qint32 transposea = False transposeb = False Tactivation = tf.quint8 a = tf.constant7,...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`

ImpactIf 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.pythonimport tensorflow as tfnumbits = 8narrowrange = Falseinputs = tf.constant0, shape=2,3, dtype=tf.float32min = tf.constant0,...

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"...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`

ImpactWhen 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.pythonimport tensorflow as tfarg0=tf.random.uniformshape=1,1, dtype=tf.float32,...

TensorFlow vulnerable to `CHECK` fail in `AvgPoolGrad`

ImpactThe 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:pythonimport tensorflow as tfksize = 1, 2, 2, 1strides = 1, 2, 2, 1padding = "VALID"dataformat = "NHWC"originputshape =...

TensorFlow vulnerable to `CHECK` fail in `SetSize`

ImpactWhen 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.pythonimport tensorflow as tfarg0=1arg1=1,1arg2=1arg3=Truearg4=''tf.rawops.SetSizesetindices=arg0, setvalues=arg1, setshape=arg2,...

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...

TensorFlow vulnerable to `CHECK` failures in `FractionalAvgPoolGrad`

ImpactThe 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.pythonimport tensorflow as tfoverlapping = Trueoriginputtensorshape =...

TensorFlow vulnerable to null dereference on MLIR on empty function attributes

ImpactEig can be fed an incorrect Tout input, resulting in a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as np arg0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2, dtype=tf.float32arg1=tf.complex128arg2=Truearg3=''tf.rawops.Eiginput=arg...

TensorFlow vulnerable to floating point exception in `Conv2D`

ImpactIf 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.pythonimport tensorflow as tfimport numpy as npwith tf.device"CPU": also can be...

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

ImpactWhen mlir::tfg::GraphDefImporter::ConvertNodeDef tries to convert NodeDefs without an op name, it crashes.cppStatus GraphDefImporter::ConvertNodeDefOpBuilder , ConversionState , const NodeDef VLOG4 opdef; else auto it = functionopdefs.findnode.op; if it == functionopdefs.end return...

TensorFlow vulnerable to `CHECK` fail in `Unbatch`

ImpactWhen Unbatch receives a nonscalar input id, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as nparg0=tf.constantvalue=np.random.randomsize=3, 3, 1, dtype=tf.float64arg1=tf.constantvalue=np.random.randint0,100,size=3, 3, 1,...

TensorFlow vulnerable to `CHECK` fail in `Unbatch`

ImpactWhen Unbatch receives a nonscalar input id, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as nparg0=tf.constantvalue=np.random.randomsize=3, 3, 1, dtype=tf.float64arg1=tf.constantvalue=np.random.randint0,100,size=3, 3, 1,...

PYSEC-2026-3354 TensorFlow vulnerable to `CHECK` fail in `tf.random.gamma`

Impact When tf.random.gamma receives large input shape and rates, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=4,, dtype=tf.int32, maxval=65536 arg1=tf.random.uniformshape=4, 4, dtype=tf.float64, maxval=None...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsGradient`

ImpactWhen tf.quantization.fakequantwithminmaxvarsgradient receives input min or max that is nonscalar, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as np arg0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2,...

TensorFlow vulnerable to `CHECK` fail in `tf.random.gamma`

ImpactWhen tf.random.gamma receives large input shape and rates, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfarg0=tf.random.uniformshape=4,, dtype=tf.int32, maxval=65536arg1=tf.random.uniformshape=4, 4, dtype=tf.float64,...