PT-2026-59711

Impact When Conv2DBackpropInput receives empty out backprop 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 input sizes = 3, 1, 1, 2 filter...

PT-2026-59840

Impact The implementation of SparseTensorSliceDataset has an undefined behavior: under certain condition it can be made to dereference a nullptr value: python import tensorflow as tf import numpy as np tf.raw ops.SparseTensorSliceDataset indices=, values=, dense shape=1,1 The 3 input arguments...

PT-2026-59763

Impact An attacker can craft a TFLite model that would cause an integer overflow in embedding lookup operations: cc int embedding size = 1; int lookup size = 1; for int i = 0; i data.i32i; lookup size = dim; output shape-datak = dim; for int i = 1; i datak = dim; Both embedding size and lookup si...

PT-2026-59752

Impact The implementation of GetInitOp is vulnerable to a crash caused by dereferencing a null pointer: cc const auto& init op sig it = meta graph def.signature def.findkSavedModelInitOpSignatureKey; if init op sig it != sig def map.end init op name = init op sig it-second.outputs...

PT-2026-59726

Impact The tf.compat.v1.signal.rfft2d and tf.compat.v1.signal.rfft3d lack input validation and under certain condition can result in crashes due to CHECK-failures. Patches We have patched the issue in GitHub commit 0a8a781e597b18ead006d19b7d23d0a369e9ad73 merging GitHub PR 55274. The fix will be...

PT-2026-59796

Impact The implementation of tf.raw ops.GetSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack: python import tensorflow as tf handle = tf.constant"", shape=0, dtype=tf.string tf.raw...

PT-2026-59714

Impact An attacker can craft a TFLite model that would trigger a division by zero in the implementation of depthwise convolutions. The parameters of the convolution can be user controlled and are also used within a division operation to determine the size of the padding that needs to be added...

PT-2026-59785

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...

PT-2026-59777

Impact The implementation of OpLevelCostEstimator::CalculateTensorSize is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements: cc int64 t OpLevelCostEstimator::CalculateTensorSize const OpInfo::TensorProperties...

PT-2026-59831

Impact The implementation of tf.raw ops.SparseTensorToCSRSparseMatrix does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack: python import tensorflow as tf indices = tf.constant53, shape=3, dtype=tf.int64 values =...

PT-2026-59843

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...

PT-2026-59765

Impact An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. Patches We have patched t...

PT-2026-59842

Impact A GraphDef from a TensorFlow SavedModel can be maliciously altered to cause a TensorFlow process to crash due to encountering a StatusOr value that is an error and forcibly extracting the value from it: cc if op reg data-type ctor != nullptr VLOG3 op def; const FullTypeDef ctor typedef =...

PT-2026-59895

Impact Multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid: python import tensorflow as tf tf.raw ops.QueueIsClosedV2handle= python import tensorflow as tf tf.summary.flushwriter= In graph mode, it would have been impossible to perform these...

PT-2026-59869

Impact The implementation of OpLevelCostEstimator::CalculateOutputSize is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements: cc for const auto& dim : output shape.dim output size = dim.size; Here, we can have ...

PT-2026-59948

Impact The implementation of tf.raw ops.QuantizeAndDequantizeV4Grad does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack: python import tensorflow as tf tf.raw ops.QuantizeAndDequantizeV4Grad gradients=tf.constant1,...

PT-2026-59949

Impact The implementation of tf.raw ops.StagePeek does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack: python import tensorflow as tf index = tf.constant, shape=0, dtype=tf.int32 tf.raw ops.StagePeekindex=index,...

PT-2026-59950

Impact The implementation of tf.raw ops.DeleteSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack: python import tensorflow as tf handle = tf.constant"", shape=0, dtype=tf.string tf.raw...

PT-2026-59875

Impact The implementation of tf.histogram fixed width is vulnerable to a crash when the values array contain NaN elements: python import tensorflow as tf import numpy as np tf.histogram fixed widthvalues=np.nan, value range=1,2 The implementation assumes that all floating point operations are...

PT-2026-59856

Impact Under certain scenarios, TensorFlow can fail to specialize a type during shape inference: cc void InferenceContext::PreInputInit const OpDef& op def, const std::vector& input tensors, const std::vector& input tensors as shapes const auto ret = full type::SpecializeTypeattrs , op def;...