7218 matches found
TensorFlow has Floating Point Exception in AudioSpectrogram
Impactversion:2.11.0 //core/ops/audioops.cc:70Status SpectrogramShapeFnInferenceContext c ShapeHandle input; TFRETURNIFERRORc-WithRankc-input0, 2, ; int32t windowsize; TFRETURNIFERRORc-GetAttr"windowsize", size; int32t stride; TFRETURNIFERRORc-GetAttr"stride", ; .....1DimensionHandle inputlength ...
TensorFlow has Null Pointer Error in SparseSparseMaximum
ImpactWhen SparseSparseMaximum is given invalid sparse tensors as inputs, it can give an NPE. pythonimport tensorflow as tftf.rawops.SparseSparseMaximum aindices=1, avalues = 0.1 , ashape = 2, bindices=, bvalues =2 , bshape = 2, PatchesWe have patched the issue in GitHub commit...
TensorFlow has Null Pointer Error in LookupTableImportV2
ImpactThe function tf.rawops.LookupTableImportV2 cannot handle scalars in the values parameter and gives an NPE.pythonimport tensorflow as tfv = [email protected]=Truedef test: func = tf.rawops.LookupTableImportV2 para='tablehandle': v.handle,'keys': 62.98910140991211,...
TensorFlow has Null Pointer Error in LookupTableImportV2
ImpactThe function tf.rawops.LookupTableImportV2 cannot handle scalars in the values parameter and gives an NPE.pythonimport tensorflow as tfv = [email protected]=Truedef test: func = tf.rawops.LookupTableImportV2 para='tablehandle': v.handle,'keys': 62.98910140991211,...
TensorFlow has Null Pointer Error in RandomShuffle with XLA enable
ImpactNPE in RandomShuffle with XLA enable pythonimport tensorflow as tffunc = tf.rawops.RandomShufflepara = 'value': 1e+20, 'seed': -4294967297, 'seed2': [email protected]=Truedef test: y = funcpara return ytest PatchesWe have patched the issue in GitHub commit...
TensorFlow has Null Pointer Error in RandomShuffle with XLA enable
ImpactNPE in RandomShuffle with XLA enable pythonimport tensorflow as tffunc = tf.rawops.RandomShufflepara = 'value': 1e+20, 'seed': -4294967297, 'seed2': [email protected]=Truedef test: y = funcpara return ytest PatchesWe have patched the issue in GitHub commit...
TensorFlow vulnerable to Out-of-Bounds Read in GRUBlockCellGrad
ImpactOut of bounds read in GRUBlockCellGradpythonfunc = tf.rawops.GRUBlockCellGradpara = 'x': 21.1, 156.2, 83.3, 115.4, 'hprev': array136.5, 136.6, 'wru': array26.7, 0.8, 47.9, 26.1, 26.2, 26.3, 'wc': array 0.4, 31.5, 0.6, 'bru': array0.1, 0.2 , dtype=float32, 'bc': 0x41414141, 'r': array0.3, 0....
TensorFlow has null dereference on ParallelConcat with XLA
ImpactWhen running with XLA, tf.rawops.ParallelConcat segfaults with a nullptr dereference when given a parameter shape with rank that is not greater than zero.pythonimport tensorflow as tffunc = tf.rawops.ParallelConcatpara = 'shape': 0, 'values': [email protected]=Truedef test: y = funcpa...
OpenStack Cinder, glance, and Nova vulnerable to Path Traversal
An issue was discovered in OpenStack Cinder before 19.1.2, 20.x before 20.0.2, and 21.0.0; Glance before 23.0.1, 24.x before 24.1.1, and 25.0.0; and Nova before 24.1.2, 25.x before 25.0.2, and 26.0.0. By supplying a specially created VMDK flat image that references a specific backing file path, a...
Segfault in `CompositeTensorVariantToComponents`
ImpactAn input encoded that is not a valid CompositeTensorVariant tensor will trigger a segfault in tf.rawops.CompositeTensorVariantToComponents.pythonimport tensorflow as tfencode = tf.rawops.EmptyTensorListelementdtype=tf.int32, elementshape=10, 15, maxnumelements=2meta=...
Overflow in `ResizeNearestNeighborGrad`
ImpactWhen tf.rawops.ResizeNearestNeighborGrad is given a large size input, it overflows.import tensorflow as tfaligncorners = Truehalfpixelcenters = Falsegrads = tf.constant1, shape=1,8,16,3, dtype=tf.float16size = tf.constant1879048192,1879048192, shape=2,...
`CHECK` fail via inputs in `SparseFillEmptyRowsGrad`
ImpactIf SparseFillEmptyRowsGrad is given empty inputs, TensorFlow will crash.pythonimport tensorflow as tftf.rawops.SparseFillEmptyRowsGrad reverseindexmap=, gradvalues=, name=None PatchesWe have patched the issue in GitHub commit af4a6a3c8b95022c351edae94560acc61253a1b8.The fix will be included...
`CHECK_EQ` fail via input in `SparseMatrixNNZ`
ImpactAn input sparsematrix that is not a matrix with a shape with rank 0 will trigger a CHECK fail in tf.rawops.SparseMatrixNNZ.pythonimport tensorflow as tftf.rawops.SparseMatrixNNZsparsematrix= PatchesWe have patched the issue in GitHub commit f856d02e5322821aad155dad9b3acab1e9f5d693.The fix...
`FractionalMaxPoolGrad` Heap out of bounds read
ImpactIf FractionMaxPoolGrad is given outsize inputs rowpoolingsequence and colpoolingsequence, TensorFlow will crash.pythonimport tensorflow as tftf.rawops.FractionMaxPoolGrad originput = 1, 1, 1, 1, 1, origoutput = 1, 1, 1, outbackprop = 3, 3, 6, rowpoolingsequence = -0x4000000, 1, 1,...
Overflow in `tf.keras.losses.poisson`
Impacttf.keras.losses.poisson receives a ypred and ytrue that are passed through functor::mul in BinaryOp. If the resulting dimensions overflow an int32, TensorFlow will crash due to a size mismatch during broadcast assignment.pythonimport numpy as npimport tensorflow as tftruevalue =...
`CHECK` fail in `BCast` overflow
ImpactIf BCast::ToShape is given input larger than an int32, it will crash, despite being supposed to handle up to an int64. An example can be seen in tf.experimental.numpy.outer by passing in large input to the input b.pythonimport tensorflow as tfvalue = tf.constantshape=2, 1024, 1024, 1024,...
OpenStack Sushy-Tools and VirtualBMC Improper Preservation of Permissions
An issue was discovered in OpenStack Sushy-Tools through 0.21.0 and VirtualBMC through 2.2.2. Changing the boot device configuration with these packages removes password protection from the managed libvirt XML domain. NOTE: this only affects an "unsupported, production-like configuration."...
Overflow in `FusedResizeAndPadConv2D`
ImpactWhen tf.rawops.FusedResizeAndPadConv2D is given a large tensor shape, it overflows.pythonimport tensorflow as tfmode = "REFLECT"strides = 1, 1, 1, 1padding = "SAME"resizealigncorners = Falseinput = tf.constant147, shape=3,3,1,1, dtype=tf.float16size = tf.constant1879048192,1879048192,...
Overflow in `ImageProjectiveTransformV2`
ImpactWhen tf.rawops.ImageProjectiveTransformV2 is given a large output shape, it overflows.pythonimport tensorflow as tfinterpolation = "BILINEAR"fillmode = "REFLECT"images = tf.constant0.184634328, shape=2,5,8,3, dtype=tf.float32transforms = tf.constant0.378575385, shape=2,8,...
Seg fault in `ndarray_tensor_bridge` due to zero and large inputs
ImpactIf a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. E.g. the following raises an error:pythonnp.ones0, 231, 231An example of a proof of concept:pythonimport numpy as npimport tensorflow as tfinputval =...
TensorFlow vulnerable to `CHECK` fail in `ParameterizedTruncatedNormal`
ImpactParameterizedTruncatedNormal 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.pythonimport tensorflow as tfseed = 1618seed2 = 0shape = tf.random.uniformshape=3, minval=-10000,...
TensorFlow vulnerable to segfault in `SparseBincount`
ImpactIf SparseBincount is given inputs for indices, values, and denseshape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfbinaryoutput = Trueindices = tf.random.uniformshape=, minval=-10000,...
TensorFlow vulnerable to segfault in `QuantizeDownAndShrinkRange`
ImpactIf QuantizeDownAndShrinkRange is given nonscalar inputs for inputmin or inputmax, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfouttype = tf.quint8input = tf.constant1, shape=3, dtype=tf.qint32inputmin = tf.constant, shape=0,...
TensorFlow vulnerable to `CHECK` fail in `FractionalMaxPoolGrad`
ImpactFractionalMaxPoolGrad validates its inputs with CHECK failures instead of with returning errors. If it gets incorrectly sized inputs, the CHECK failure can be used to trigger a denial of service attack:pythonimport tensorflow as tfoverlapping = Trueoriginput = tf.constant.453409232,...
TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`
ImpactThe implementation of Conv2DBackpropInput requires inputsizes to be 4-dimensional. Otherwise, it gives a CHECK failure which can be used to trigger a denial of service attack:pythonimport tensorflow as tfstrides = 1, 1, 1, 1padding = "SAME"usecudnnongpu = Trueexplicitpaddings = dataformat =...
TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`
ImpactThe implementation of Conv2DBackpropInput requires inputsizes to be 4-dimensional. Otherwise, it gives a CHECK failure which can be used to trigger a denial of service attack:pythonimport tensorflow as tfstrides = 1, 1, 1, 1padding = "SAME"usecudnnongpu = Trueexplicitpaddings = dataformat =...
TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`
ImpactIf FakeQuantWithMinMaxVars is given min or max tensors of a nonzero rank, it results in a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfnumbits = 8narrowrange = Falseinputs = tf.constant0, shape=2,3, dtype=tf.float32min = tf.constant0,...
TensorFlow vulnerable to segfault in `QuantizedBiasAdd`
ImpactIf QuantizedBiasAdd is given mininput, maxinput, minbias, maxbias tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfouttype = tf.qint32input = tf.constant85,170,255, shape=3, dtype=tf.quint8bias =...
TensorFlow vulnerable to segfault in `QuantizedBiasAdd`
ImpactIf QuantizedBiasAdd is given mininput, maxinput, minbias, maxbias tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfouttype = tf.qint32input = tf.constant85,170,255, shape=3, dtype=tf.quint8bias =...
TensorFlow vulnerable to segfault in `QuantizedAdd`
ImpactIf QuantizedAdd is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfToutput = tf.qint32x = tf.constant140, shape=1, dtype=tf.quint8y = tf.constant26, shape=10, dtype=tf.quint8mi...
TensorFlow vulnerable to segfault in `LowerBound` and `UpperBound`
ImpactIf LowerBound or UpperBound is given an emptysortedinputs input, it results in a nullptr dereference, leading to a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfouttype = tf.int32sortedinputs = tf.constant, shape=10,0, dtype=tf.float32values =...
TensorFlow vulnerable to segfault in `BlockLSTMGradV2`
ImpactThe implementation of BlockLSTMGradV2 does not fully validate its inputs. - wci, wcf, wco, b must be rank 1 - w, csprev, hprev must be rank 2 - x must be rank 3This results in a a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfusepeephole =...
TensorFlow vulnerable to `CHECK` failures in `FractionalAvgPoolGrad`
ImpactThe 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.pythonimport tensorflow as tfoverlapping = Trueoriginputtensorshape =...
TensorFlow vulnerable to Int overflow in `RaggedRangeOp`
ImpactThe RaggedRangOp function takes an argument limits that is eventually used to construct a TensorShape as an int64. If limits is a very large float, it can overflow when converted to an int64. This triggers an InvalidArgument but also throws an abort signal that crashes the...
TensorFlow vulnerable to Int overflow in `RaggedRangeOp`
ImpactThe RaggedRangOp function takes an argument limits that is eventually used to construct a TensorShape as an int64. If limits is a very large float, it can overflow when converted to an int64. This triggers an InvalidArgument but also throws an abort signal that crashes the...
TensorFlow vulnerable to floating point exception in `Conv2D`
ImpactIf 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.pythonimport tensorflow as tfimport numpy as npwith tf.device"CPU": also can be...
TensorFlow vulnerable to null dereference on MLIR on empty function attributes
ImpactWhen 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 = "tf."...
TensorFlow vulnerable to null dereference on MLIR on empty function attributes
ImpactWhen 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 = "tf."...
TensorFlow vulnerable to `CHECK`-fail in `tensorflow::full_type::SubstituteFromAttrs`
ImpactWhen tensorflow::fulltype::SubstituteFromAttrs receives a FullTypeDef& t that is not exactly three args, it triggers a CHECK-fail instead of returning a status.cppStatus SubstituteForEachAttrMap& attrs, FullTypeDef& t DCHECKEQt.argssize, 3; const auto& cont = t.args0; const auto& tmpl =...
TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsGradient`
ImpactWhen tf.quantization.fakequantwithminmaxvarsgradient receives input min or max that is nonscalar, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as np arg0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2,...
TensorFlow vulnerable to `CHECK` fail in `RandomPoissonV2`
ImpactWhen RandomPoissonV2 receives large input shape and rates, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfarg0=tf.random.uniformshape=4,, dtype=tf.int32, maxval=65536arg1=tf.random.uniformshape=4, 4, 4, 4, 4, dtype=tf.float32,...
TensorFlow vulnerable to `CHECK` fail in `DenseBincount`
ImpactDenseBincount 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.pythonimport tensorflow as tfbinaryoutput = Trueinput =...
TensorFlow vulnerable to integer overflow in math ops
ImpactWhen RangeSize receives values that do not fit into an int64t, it crashes.cpp auto size = std::isintegral::value ? Eigen::numext::abslimit - start + Eigen::numext::absdelta - T1 / Eigen::numext::absdelta : Eigen::numext::ceil Eigen::numext::abslimit - start / delta; // This check does not...
TensorFlow segfault TFLite converter on per-channel quantized transposed convolutions
ImpactWhen converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process.pythonimport tensorflow as tfclass QuantConv2DTransposedtf.keras.layers.Layer: def buildself, inputshape: self.kernel = self.addweight"kernel", 3, 3,...
PYSEC-0000-CVE-2026-56259
Crawl4AI before 0.8.8 contains credential exfiltration vulnerabilities in the Docker API server that allow attackers to redirect LLM API calls to attacker-controlled endpoints and read arbitrary environment variables. Attackers can exploit the unauthenticated /md, /llm, and /llm/job endpoints by...
TensorFlow vulnerable to `CHECK` failure in `SobolSample` via missing validation
ImpactThe 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.pythonimport tensorflow as tftf.rawops.SobolSampledim=tf.constant1,0, numresults=tf.constant1, skip=tf.constant1 PatchesWe...
TensorFlow vulnerable to `CHECK` failure in tf.reshape via overflows
ImpactThe 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:pythonimport tensorflow as tftf.reshapetensor=1,shape=tf.constant0 for i in range255, dtype=tf.int64This is...
TensorFlow vulnerable to OOB read in `Gather_nd` in TF Lite
ImpactThe 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. PatchesWe have patched the issue in GitHub commit...
TensorFlow vulnerable to `CHECK` failure in tf.reshape via overflows
ImpactThe 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:pythonimport tensorflow as tftf.reshapetensor=1,shape=tf.constant0 for i in range255, dtype=tf.int64This is...
TensorFlow vulnerable to `CHECK` failure in `SobolSample` via missing validation
ImpactThe 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.pythonimport tensorflow as tftf.rawops.SobolSampledim=tf.constant1,0, numresults=tf.constant1, skip=tf.constant1 PatchesWe...