PT-2026-59870

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-2026-59845

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...

PT-2026-59922

Impact When tf.linalg.matrix rank receives an empty input a, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf a = tf.constant, shape=0, 1, 1, dtype=tf.float32 tf.linalg.matrix ranka=a Patches We have patched the issue in GitH...

PT-2026-59975

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...

PT-2026-59786

Impact version:2.11.0 //core/ops/audio ops.cc:70 Status SpectrogramShapeFnInferenceContext c ShapeHandle input; TF RETURN IF ERRORc-WithRankc-input0, 2, &input; int32 t window size; TF RETURN IF ERRORc-GetAttr"window size", &window size; int32 t stride; TF RETURN IF ERRORc-GetAttr"stride", &strid...

PT-2026-59918

Impact If QuantizeAndDequantizeV3 is given a nonscalar num bits input tensor, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf signed input = True range given = False narrow range = False axis = -1 input = tf.constant-3.5, shape=1,...

PT-2026-59799

Impact A malicious invalid input crashes a tensorflow model Check Failed and can be used to trigger a denial of service attack. To minimize the bug, we built a simple single-layer TensorFlow model containing a Convolution3DTranspose layer, which works well with expected inputs and can be deployed...

PT-2026-59878

Impact The implementation of AvgPoolGrad does not fully validate the input orig input shape. 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" data format = "NHWC" orig...

PT-2026-59872

Impact The implementation of AvgPool3DGradOp does not fully validate the input orig input shape. 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 paddin...

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-2026-59712

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-2026-59717

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...