864 matches found
PYSEC-2026-3248 TensorFlow vulnerable to `CHECK` fail in `TensorListScatter` and `TensorListScatterV2`
Impact When TensorListScatter and TensorListScatterV2 receive an elementshape of a rank greater than one, they give a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=2, 2, 2, dtype=tf.float16, maxval=None...
PYSEC-2026-3296 TensorFlow vulnerable to `CHECK` failures in `FractionalAvgPoolGrad`
Impact The 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. python import tensorflow as tf overlapping = True originputtensorshape =...
PYSEC-2026-3133 TensorFlow vulnerable to `CHECK` failures in `FractionalAvgPoolGrad`
Impact The 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. python import tensorflow as tf overlapping = True originputtensorshape =...
PYSEC-2026-3257 TensorFlow vulnerable to `CHECK` failures in `AvgPool3DGrad`
Impact The implementation of AvgPool3DGradOp does not fully validate the input originputshape. 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 padding ...
PYSEC-2026-3311 TensorFlow vulnerable to `CHECK` fail in `RandomPoissonV2`
Impact When RandomPoissonV2 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, 4, 4, 4, dtype=tf.float32, maxval=None...
PYSEC-2026-3377 TensorFlow vulnerable to `CHECK` fail in `DenseBincount`
Impact DenseBincount assumes its input tensor weights to either have the same shape as its input tensor input or to be length-0. A different weights shape will trigger a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf binaryoutput = True input =...
PYSEC-2026-3350 Missing validation causes denial of service via `SparseTensorToCSRSparseMatrix`
Impact The implementation of tf.rawops.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 =...
PYSEC-2026-3211 Type confusion leading to segfault in Tensorflow
Impact The implementation of shape inference for ConcatV2 can be used to trigger a denial of service attack via a segfault caused by a type confusion: python import tensorflow as tf @tf.function def test: y = tf.rawops.ConcatV2 values=1,2,3,4,5,6, axis = 0xb500005b return y test The axis argument...
PYSEC-2026-3240 Integer overflows in Tensorflow
Impact The implementations of SparseCwise ops are vulnerable to integer overflows. These can be used to trigger large allocations so, OOM based denial of service or CHECK-fails when building new TensorShape objects so, assert failures based denial of service: python import tensorflow as tf import...
PYSEC-2026-3204 Reachable Assertion in Tensorflow
Impact When decoding a tensor from protobuf, a TensorFlow process can encounter cases where a CHECK assertion is invalidated based on user controlled arguments, if the tensors have an invalid dtype and 0 elements or an invalid shape. This allows attackers to cause denial of services in TensorFlow...
PYSEC-2026-3241 Crash when type cannot be specialized in Tensorflow
Impact Under certain scenarios, TensorFlow can fail to specialize a type during shape inference: cc void InferenceContext::PreInputInit const OpDef& opdef, const std::vector& inputtensors, const std::vector& inputtensorsasshapes const auto ret = fulltype::SpecializeTypeattrs, opdef;...
PYSEC-2026-3121 Out of bounds read in Tensorflow
Impact The implementation of shape inference for ReverseSequence does not fully validate the value of batchdim and can result in a heap OOB read: python import tensorflow as tf @tf.function def test: y = tf.rawops.ReverseSequence input = 'aaa','bbb', seqlengths = 1,1,1, seqdim = -10, batchdim = -...
PYSEC-2026-3159 Integer overflow in Tensorflow
Impact The implementation of shape inference for Dequantize is vulnerable to an integer overflow weakness: python import tensorflow as tf input = tf.constant1,1,dtype=tf.qint32 @tf.function def test: y = tf.rawops.Dequantize input=input, minrange=1.0, maxrange=10.0, mode='MINCOMBINED',...
PYSEC-2026-3113 Abort caused by allocating a vector that is too large in Tensorflow
Impact During shape inference, TensorFlow can allocate a large vector based on a value from a tensor controlled by the user: cc const auto numdims = Valueshapedim; std::vector dims; dims.reservenumdims; Patches We have patched the issue in GitHub commit 1361fb7e29449629e1df94d44e0427ebec8c83c7. T...
PYSEC-2026-2019 vLLM vulnerable to DoS with incorrect shape of multimodal embedding inputs
Summary Users can crash the vLLM engine serving multimodal models by passing multimodal embedding inputs with correct ndim but incorrect shape e.g. hidden dimension is wrong, regardless of whether the model is intended to support such inputs as defined in the Supported Models page. The issue has...
PYSEC-2026-1958 TensorFlow vulnerable to integer overflow in EditDistance
Impact TFversion 2.11.0 //tensorflow/core/ops/arrayops.cc:1067 const Tensor hypothesisshapet = c-inputtensor2; std::vector dimshypothesisshapet-NumElements - 1; for int i = 0; i MakeDimstd::maxhvaluesi, tvaluesi; if hypothesisshapet is empty, hypothesisshapet-NumElements - 1 will be integer...
PYSEC-2026-1959 TensorFlow vulnerable to Out-of-Bounds Read in DynamicStitch
Impact If the parameter indices for DynamicStitch does not match the shape of the parameter data, it can trigger an stack OOB read. python import tensorflow as tf func = tf.rawops.DynamicStitch para='indices': 0xdeadbeef, 405, 519, 758, 1015, 'data': 110.27793884277344, 120.29475402832031,...
PYSEC-2026-957 Segfault in `tf.raw_ops.TensorListConcat`
Impact If tf.rawops.TensorListConcat is given elementshape=, it results segmentation fault which can be used to trigger a denial of service attack. python import tensorflow as tf tf.rawops.TensorListConcat inputhandle=tf.data.experimental.tovarianttf.data.Dataset.fromtensorslices1, 2, 3,...
PYSEC-2026-951 Overflow in `ImageProjectiveTransformV2`
Impact When tf.rawops.ImageProjectiveTransformV2 is given a large output shape, it overflows. python import tensorflow as tf interpolation = "BILINEAR" fillmode = "REFLECT" images = tf.constant0.184634328, shape=2,5,8,3, dtype=tf.float32 transforms = tf.constant0.378575385, shape=2,8,...
PYSEC-2026-1023 TensorFlow vulnerable to `CHECK` fail in `ParameterizedTruncatedNormal`
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,...