MobSF allows attackers to read arbitrary files via a crafted HTTP request

Mobile Security Framework MobSF v0.9.2 and below was discovered to contain a local file inclusion LFI vulnerability in the StaticAnalyzer/views.py script. This vulnerability allows attackers to read arbitrary files via a crafted HTTP request...

Ansible leaks password to logs

A flaw was found in Ansible in the amazon.aws collection when using the towercallback parameter from the amazon.aws.ec2instance module. This flaw allows an attacker to take advantage of this issue as the module is handling the parameter insecurely, leading to the password leaking in the logs...

Plaintext storage of tokens in pulp_ansible

The collection remote for pulpansible stores tokens in plaintext instead of using pulp's encrypted field and exposes them in read/write mode via the API instead of marking it as write only...

TensorFlow vulnerable to `CHECK` fail in `tf.linalg.matrix_rank`

ImpactWhen tf.linalg.matrixrank receives an empty input a, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfa = tf.constant, shape=0, 1, 1, dtype=tf.float32tf.linalg.matrixranka=a PatchesWe have patched the issue in GitHub commi...

TensorFlow vulnerable to segfault in `RaggedBincount`

ImpactIf RaggedBincount is given an empty input tensor splits, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfbinaryoutput = Truesplits = tf.random.uniformshape=0, minval=-10000, maxval=10000, dtype=tf.int64, seed=-7430values =...

TensorFlow vulnerable to segfault in `QuantizedRelu` and `QuantizedRelu6`

ImpactIf QuantizedRelu or QuantizedRelu6 are given nonscalar inputs for minfeatures or maxfeatures, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfouttype = tf.quint8features = tf.constant28, shape=4,2, dtype=tf.quint8minfeatures =...

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 `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 `QuantizedMatMul`

ImpactIf QuantizedMatMul is given nonscalar input for: - mina - maxa - minb - maxbIt gives a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfToutput = tf.qint32transposea = Falsetransposeb = FalseTactivation = tf.quint8a = tf.constant7, shape=3,4,...

TensorFlow vulnerable to `CHECK` fail in `LRNGrad`

ImpactIf LRNGrad is given an outputimage input tensor that is not 4-D, it results in a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfdepthradius = 1bias = 1.59018219alpha = 0.117728651beta = 0.404427052inputgrads = tf.random.uniformshape=4, 4, 4, 4...

TensorFlow vulnerable to segfault in `QuantizedInstanceNorm`

ImpactIf QuantizedInstanceNorm is given xmin or xmax tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfoutputrangegiven = Falsegivenymin = 0givenymax = 0varianceepsilon = 1e-05minseparation = 0.001x =...

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 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 `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 `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 `CHECK` fail in `MaxPool`

ImpactWhen MaxPool receives a window size input array ksize with dimensions greater than its input tensor input, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as npinput = np.ones1, 1, 1, 1ksize = 1, 1, 2, 2strid...

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 `AvgPoolGrad`

ImpactThe implementation of AvgPoolGrad does not fully validate the input originputshape. This results in a CHECK failure which can be used to trigger a denial of service attack:pythonimport tensorflow as tfksize = 1, 2, 2, 1strides = 1, 2, 2, 1padding = "VALID"dataformat = "NHWC"originputshape =...

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 `CHECK` fail in `TensorListFromTensor`

ImpactWhen TensorListFromTensor receives an elementshape of a rank greater than one, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfarg0=tf.random.uniformshape=6, 6, 2, dtype=tf.bfloat16, maxval=Nonearg1=tf.random.uniformshape=6, 9, 1, 3,...

TensorFlow vulnerable to `CHECK` failures in `AvgPool3DGrad`

ImpactThe 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:pythonimport tensorflow as tfksize = 1, 1, 1, 1, 1strides = 1, 1, 1, 1, 1padding =...

TensorFlow vulnerable to segfault in `QuantizedAvgPool`

ImpactIf QuantizedAvgPool 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 tfksize = 1, 2, 2, 1strides = 1, 2, 2, 1padding = "SAME"input = tf.constant1, shape=1,4,4,2,...

TensorFlow vulnerable to `CHECK` fail in `TensorListScatter` and `TensorListScatterV2`

ImpactWhen 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.pythonimport tensorflow as tfarg0=tf.random.uniformshape=2, 2, 2, dtype=tf.float16, maxval=Nonearg1=tf.random.uniformshape=2,...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`

ImpactWhen tf.quantization.fakequantwithminmaxvarsperchannelgradient receives input min or max of rank other than 1, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfarg0=tf.random.uniformshape=1,1, dtype=tf.float32,...

TensorFlow vulnerable to `CHECK` failure in `TensorListReserve` via missing validation

ImpactIn core/kernels/listkernels.cc's TensorListReserve, numelements is assumed to be a tensor of size 1. When a numelements of more than 1 element is provided, then tf.rawops.TensorListReserve fails the CHECKEQ in CheckIsAlignedAndSingleElement.pythonimport tensorflow as...

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 `CHECK` fail in `CollectiveGather`

ImpactWhen CollectiveGather receives an scalar input input, it gives a CHECK fails that can be used to trigger a denial of service attack.pythonimport tensorflow as tfarg0=1arg1=1arg2=1arg3=1arg4=3, 3,3arg5='auto'arg6=0arg7=''tf.rawops.CollectiveGatherinput=arg0, groupsize=arg1, groupkey=arg2,...

TensorFlow vulnerable to `CHECK` fail in `SetSize`

ImpactWhen SetSize receives an input setshape that is not a 1D tensor, it gives a CHECK fails that can be used to trigger a denial of service attack.pythonimport tensorflow as tfarg0=1arg1=1,1arg2=1arg3=Truearg4=''tf.rawops.SetSizesetindices=arg0, setvalues=arg1, setshape=arg2,...

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 `UnbatchGradOp`

ImpactThe UnbatchGradOp function takes an argument id that is assumed to be a scalar. A nonscalar id can trigger a CHECK failure and crash the program.pythonimport numpy as npimport tensorflow as tf id is not scalartf.rawops.UnbatchGradoriginalinput= tf.constant1,batchindex=tf.constant0,0,0 , ,...

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 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 null dereference on MLIR on empty function attributes

ImpactEig can be fed an incorrect Tout input, resulting in 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, dtype=tf.float32arg1=tf.complex128arg2=Truearg3=''tf.rawops.Eiginput=arg...

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 `EmptyTensorList`

ImpactIf EmptyTensorList receives an input elementshape with more than one dimension, it gives a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tftf.rawops.EmptyTensorListelementshape=tf.onesdtype=tf.int32, shape=1, 0,...

TensorFlow vulnerable to assertion fail on MLIR empty edge names

ImpactWhen mlir::tfg::ConvertGenericFunctionToFunctionDef is given empty function attributes, it crashes.cpp// We pre-allocate the array of operands and populate it using the// outputnametoposition and controloutputtoposition populated// previously.SmallVector retvalsfunc.retsize +...

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 null-dereference in `mlir::tfg::GraphDefImporter::ConvertNodeDef`

ImpactWhen mlir::tfg::GraphDefImporter::ConvertNodeDef tries to convert NodeDefs without an op name, it crashes.cppStatus GraphDefImporter::ConvertNodeDefOpBuilder , ConversionState , const NodeDef VLOG4 opdef; else auto it = functionopdefs.findnode.op; if it == functionopdefs.end return...

TensorFlow vulnerable to null-dereference in `mlir::tfg::TFOp::nameAttr`

ImpactWhen mlir::tfg::TFOp::nameAttr receives null type list attributes, it crashes.cppStatusOr GraphDefImporter::ArgNumTypeconst NamedAttrList , const OpDef::ArgDef def, SmallVectorImpl // Check whether a type list attribute is specified. if !argdef.typelistattr.empty if auto v =...

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 `tf.random.gamma`

ImpactWhen tf.random.gamma 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, dtype=tf.float64,...

TensorFlow vulnerable to `CHECK` fail in `DrawBoundingBoxes`

ImpactWhen DrawBoundingBoxes receives an input boxes that is not of dtype float, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as nparg0=tf.constantvalue=np.random.randomsize=1, 3, 2, 3, shape=1, 3, 2, 3,...

TensorFlow vulnerable to `CHECK` fail in `Unbatch`

ImpactWhen Unbatch receives a nonscalar input id, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as nparg0=tf.constantvalue=np.random.randomsize=3, 3, 1, dtype=tf.float64arg1=tf.constantvalue=np.random.randint0,100,size=3, 3, 1,...

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 vulnerable to segfault in `Requantize`

ImpactIf Requantize is given inputmin, inputmax, requestedoutputmin, requestedoutputmax 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.quint8input = tf.constant1, shape=3, dtype=tf.qint32inputmin...

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 `AudioSummaryV2`

ImpactWhen AudioSummaryV2 receives an input samplerate with more than one element, it gives a CHECK fails that can be used to trigger a denial of service attack.pythonimport tensorflow as tfarg0=''arg1=tf.random.uniformshape=1,1, dtype=tf.float32, maxval=Nonearg2=tf.random.uniformshape=2,1,...

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 `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannel`

ImpactIf FakeQuantWithMinMaxVarsPerChannel is given min or max tensors of a rank other than one, 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=4, dtype=tf.float32min =...

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...