`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,...

FPE in `tf.image.generate_bounding_box_proposals`

ImpactWhen running on GPU, tf.image.generateboundingboxproposals receives a scores input that must be of rank 4 but is not checked.pythonimport tensorflow as tfa = tf.constantvalue=1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0b =...

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,...

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,...

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 `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 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 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 `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 `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 `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 `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 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 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 `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 `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 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,...

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,...

TensorFlow vulnerable to `CHECK` fail in `tf.sparse.cross`

ImpactIf 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.pythonimport tensorflow as tftf.sparse.crossinputs=,name='a',separator=tf.constant'a', 'b',dtype=tf.string PatchesWe have patched the issue in...

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...

Microsoft: CBC Padding Oracle in Azure Blob Storage Encryption Library

SummaryThe Azure Storage Encryption library in Java and other languages is vulnerable to a CBC Padding Oracle attack, similar to CVE-2020-8911. The library is not vulnerable to the equivalent of CVE-2020-8912, but only because it currently only supports AES-CBC as encryption mode. SeverityModerat...

Uncontrolled Resource Consumption in asyncua and opcua

All versions of package opcua; all versions of package asyncua are vulnerable to Denial of Service DoS due to a missing limitation on the number of received chunks - per single session or in total for all concurrent sessions. An attacker can exploit this vulnerability by sending an unlimited numb...

Segfault if `tf.histogram_fixed_width` is called with NaN values in TensorFlow

ImpactThe implementation of tf.histogramfixedwidth is vulnerable to a crash when the values array contain NaN elements:pythonimport tensorflow as tfimport numpy as nptf.histogramfixedwidthvalues=np.nan, valuerange=1,2The implementation assumes that all floating point operations are defined and th...

Missing validation causes denial of service via `Conv3DBackpropFilterV2`

ImpactThe implementation of tf.rawops.UnsortedSegmentJoin does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:pythonimport tensorflow as tftf.strings.unsortedsegmentjoin inputs='123', segmentids=0, numsegments=-1The...

Missing validation results in undefined behavior in `SparseTensorDenseAdd

ImpactThe implementation of tf.rawops.SparseTensorDenseAdd does not fully validate the input arguments:pythonimport tensorflow as tfaindices = tf.constant0, shape=17, 2, dtype=tf.int64avalues = tf.constant, shape=0, dtype=tf.float32ashape = tf.constant6, 12, shape=2, dtype=tf.int64b =...

Missing validation causes denial of service via `SparseTensorToCSRSparseMatrix`

ImpactThe 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:pythonimport tensorflow as tfindices = tf.constant53, shape=3, dtype=tf.int64values =...

Missing validation causes `TensorSummaryV2` to crash

ImpactThe implementation of tf.rawops.TensorSummaryV2 does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:pythonimport numpy as npimport tensorflow as tftf.rawops.TensorSummaryV2 tag=np.array'test', tensor=np.array3,...

XML Entity Expansion in trytond and proteus

An XML Entity Expansion XEE issue was discovered in Tryton Application Platform Server 5.x through 5.0.45, 6.x through 6.0.15, and 6.1.x and 6.2.x through 6.2.5, and Tryton Application Platform Command Line Client proteus 5.x through 5.0.11, 6.x through 6.0.4, and 6.1.x and 6.2.x through 6.2.1. A...

OpenStack Keystone and other components vulnerable to Improper Certificate Validation

HTTPSConnections in OpenStack Keystone 2013, OpenStack Compute 2013.1, and possibly other OpenStack components, fail to validate server-side SSL certificates...

Use after free in `DecodePng` kernel

ImpactA malicious user can cause a use after free behavior when decoding PNG images:ccif / ... error conditions ... / png::CommonFreeDecode; OPREQUIREScontext, false, errors::InvalidArgument"PNG size too large for int: ", decode.width, " by ", decode.height; After png::CommonFreeDecode gets calle...

Integer overflow in Tensorflow

ImpactThe implementation of Range suffers from integer overflows. These can trigger undefined behavior or, in some scenarios, extremely large allocations. PatchesWe have patched the issue in GitHub commit f0147751fd5d2ff23251149ebad9af9f03010732 merging 51733.The fix will be included in TensorFlo...

`CHECK`-failures in Tensorflow

ImpactAn attacker can trigger denial of service via assertion failure by altering a SavedModel on disk such that AttrDefs of some operation are duplicated. PatchesWe have patched the issue in GitHub commit c2b31ff2d3151acb230edc3f5b1832d2c713a9e0.The fix will be included in TensorFlow 2.8.0. We...

Division by zero in TFLite

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 befo...

Integer overflow in TFLite array creation

Impact An attacker can craft a TFLite model that would cause an integer overflow in TfLiteIntArrayCreate:ccTfLiteIntArray TfLiteIntArrayCreateint size int allocsize = TfLiteIntArrayGetSizeInBytessize; // ... TfLiteIntArray ret = TfLiteIntArraymallocallocsize; // ... The TfLiteIntArrayGetSizeInByt...

Null-dereference in Tensorflow

ImpactWhen decoding a tensor from protobuf, TensorFlow might do a null-dereference if attributes of some mutable arguments to some operations are missing from the proto. This is guarded by a DCHECK:cc const auto attr = attrs.Findarg-s; DCHECKattr != nullptr; if attr-valuecase == AttrValue::kList ...

Undefined behavior in `SparseTensorSliceDataset`

Impact The implementation of SparseTensorSliceDataset has an undefined behavior: under certain condition it can be made to dereference a nullptr value:pythonimport tensorflow as tfimport numpy as nptf.rawops.SparseTensorSliceDataset indices=, values=, denseshape=1,1The 3 input arguments represent...