PT-2026-59905

Impact When converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process. python import tensorflow as tf class QuantConv2DTransposedtf.keras.layers.Layer: def buildself, input shape: self.kernel = self.add weight"kernel", 3, 3,...

PT-2026-59745

Impact When converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process. python import tensorflow as tf class QuantConv2DTransposedtf.keras.layers.Layer: def buildself, input shape: self.kernel = self.add weight"kernel", 3, 3,...

PT-2026-59990

Impact tf.raw ops.DynamicStitch specifies input sizes when it is registered. cpp REGISTER OP"DynamicStitch" .Input"indices: N int32" .Input"data: N T" .Output"merged: T" .Attr"N : int = 1" .Attr"T : type" .SetShapeFnDynamicStitchShapeFunction; When it receives a differing number of inputs, such a...

PT-2026-59743

Impact When tf.raw ops.FusedResizeAndPadConv2D is given a large tensor shape, it overflows. python import tensorflow as tf mode = "REFLECT" strides = 1, 1, 1, 1 padding = "SAME" resize align corners = False input = tf.constant147, shape=3,3,1,1, dtype=tf.float16 size =...

PT-2026-59832

Impact The AvgPoolOp function takes an argument ksize that must be positive but is not checked. A negative ksize can trigger a CHECK failure and crash the program. python import tensorflow as tf import numpy as np value = np.ones1, 1, 1, 1 ksize = 1, 1e20, 1, 1 strides = 1, 1, 1, 1 padding = 'SAM...

PT-2026-59712

Impact If SparseBincount is given inputs for indices, values, and dense shape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf binary output = True indices = tf.random.uniformshape=,...

PT-2026-59876

Impact An input pooling ratio that is smaller than 1 will trigger a heap OOB in tf.raw ops.FractionalMaxPool and tf.raw ops.FractionalAvgPool. Patches We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also...

PT-2026-59969

Impact ParameterizedTruncatedNormal 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. python import tensorflow as tf seed = 1618 seed2 = 0 shape = tf.random.uniformshape=3, minval=-10000,...

PT-2026-59909

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 op def; else auto it = function op defs .findnode.op; if it == function op...

PT-2026-59737

Impact If QuantizedMatMul is given nonscalar input for: - min a - max a - min b - max b It gives a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf Toutput = tf.qint32 transpose a = False transpose b = False Tactivation = tf.quint8 a = tf.constant7,...

PT-2026-59900

Impact If QuantizedMatMul is given nonscalar input for: - min a - max a - min b - max b It gives a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf Toutput = tf.qint32 transpose a = False transpose b = False Tactivation = tf.quint8 a = tf.constant7,...

PT-2026-59717

Impact NPE in QuantizedMatMulWithBiasAndDequantize with MKL enable python import tensorflow as tf func = tf.raw ops.QuantizedMatMulWithBiasAndDequantize para='a': tf.constant138, dtype=tf.quint8, 'b': tf.constant4, dtype=tf.qint8, 'bias': 31.81644630432129, 47.21876525878906, 109.95201110839844,...

PT-2026-59952

Impact When tf.quantization.fake quant with min max vars per channel gradient 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 arg 0=tf.random.uniformshape=1,1, dtype=tf.float32, maxval=None arg...

PT-2026-59850

Impact When tf.quantization.fake quant with min max vars gradient receives input min or max that is nonscalar, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf import numpy as np arg 0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2,...

PT-2026-59987

Impact If QuantizeDownAndShrinkRange is given nonscalar inputs for input min or input max, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf out type = tf.quint8 input = tf.constant1, shape=3, dtype=tf.qint32 input min = tf.constant,...

PT-2026-59797

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 =...

PT-2026-59974

Impact The implementation of Conv2DBackpropInput requires input sizes 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" use cudnn on gpu = True explicit paddings =...

PT-2026-59734

Impact When ctx-step containter is a null ptr, the Lookup function will be executed with a null pointer. python import tensorflow as tf tf.raw ops.TensorArrayConcatV2handle='a', 'b', flow in = 0.1, dtype=tf.int32, element shape except0=1 Patches We have patched the issue in GitHub commit...

PT-2026-59992

Impact When SetSize receives an input set shape 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 arg 0=1 arg 1=1,1 arg 2=1 arg 3=True arg 4='' tf.raw ops.SetSizeset indices=arg 0, set values=arg 1, set shape=arg...

PT-2026-59883

Impact When tf.raw ops.ResizeNearestNeighborGrad is given a large size input, it overflows. import tensorflow as tf align corners = True half pixel centers = False grads = tf.constant1, shape=1,8,16,3, dtype=tf.float16 size = tf.constant1879048192,1879048192, shape=2, dtype=tf.int32 tf.raw...