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 write in `scatter_nd` in TF Lite

ImpactThe ScatterNd function takes an input argument that determines the indices of of the output tensor. An input index greater than the output tensor or less than zero will either write content at the wrong index or trigger a crash. 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...

TensorFlow vulnerable to OOB write in `scatter_nd` in TF Lite

ImpactThe ScatterNd function takes an input argument that determines the indices of of the output tensor. An input index greater than the output tensor or less than zero will either write content at the wrong index or trigger a crash. PatchesWe have patched the issue in GitHub commit...

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 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 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` fail in `Conv2DBackpropInput`

ImpactWhen Conv2DBackpropInput receives empty outbackprop 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.pythonimport tensorflow as tfimport numpy as npinputsizes = 3, 1, 1, 2filter =...

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...

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...

Code injection in `saved_model_cli` in TensorFlow

ImpactTensorFlow's savedmodelcli tool is vulnerable to a code injection:savedmodelcli run --inputexprs 'x=print"malicious code to run"' --dir ./--tagset serve --signaturedef servingdefaultThis can be used to open a reverse shell savedmodelcli run --inputexprs 'hello=exec"""\nimport...

Core dump when loading TFLite models with quantization in TensorFlow

ImpactCertain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling.Thus, since code was calling...

Incomplete validation in signal ops leads to crashes in TensorFlow

ImpactThe 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...

Incomplete validation in signal ops leads to crashes in TensorFlow

ImpactThe 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...

Code injection in `saved_model_cli` in TensorFlow

ImpactTensorFlow's savedmodelcli tool is vulnerable to a code injection:savedmodelcli run --inputexprs 'x=print"malicious code to run"' --dir ./--tagset serve --signaturedef servingdefaultThis can be used to open a reverse shell savedmodelcli run --inputexprs 'hello=exec"""\nimport...

Core dump when loading TFLite models with quantization in TensorFlow

ImpactCertain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling.Thus, since code was calling...

TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`

ImpactWhen Conv2DBackpropInput receives empty outbackprop 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.pythonimport tensorflow as tfimport numpy as npinputsizes = 3, 1, 1, 2filter =...

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...

Segfault and OOB write due to incomplete validation in `EditDistance` in TensorFlow

ImpactThe implementation of tf.rawops.EditDistance has incomplete validation. Users can pass negative values to cause a segmentation fault based denial of service:pythonimport tensorflow as tfhypothesisindices = tf.constant-1250999896764, shape=3, 3, dtype=tf.int64 hypothesisvalues = tf.constant0...

Heap buffer overflow due to incorrect hash function in TensorFlow

ImpactThe TensorKey hash function used total estimated AllocatedBytes, which a is an estimate per tensor, and b is a very poor hash function for constants e.g. int32t. It also tried to access individual tensor bytes through tensor.data of size AllocatedBytes. This led to ASAN failures because the...

Heap buffer overflow due to incorrect hash function in TensorFlow

ImpactThe TensorKey hash function used total estimated AllocatedBytes, which a is an estimate per tensor, and b is a very poor hash function for constants e.g. int32t. It also tried to access individual tensor bytes through tensor.data of size AllocatedBytes. This led to ASAN failures because the...

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...

Undefined behavior when users supply invalid resource handles

ImpactMultiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid:pythonimport tensorflow as tftf.rawops.QueueIsClosedV2handle=pythonimport tensorflow as tftf.summary.flushwriter= In graph mode, it would have been impossible to perform these API...

Type confusion leading to `CHECK`-failure based denial of service in TensorFlow

ImpactThe macros that TensorFlow uses for writing assertions e.g., CHECKLT, CHECKGT, etc. have an incorrect logic when comparing sizet and int values. Due to type conversion rules, several of the macros would trigger incorrectly. PatchesWe have patched the issue in GitHub commit...

Type confusion leading to `CHECK`-failure based denial of service in TensorFlow

ImpactThe macros that TensorFlow uses for writing assertions e.g., CHECKLT, CHECKGT, etc. have an incorrect logic when comparing sizet and int values. Due to type conversion rules, several of the macros would trigger incorrectly. PatchesWe have patched the issue in GitHub commit...

Undefined behavior when users supply invalid resource handles

ImpactMultiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid:pythonimport tensorflow as tftf.rawops.QueueIsClosedV2handle=pythonimport tensorflow as tftf.summary.flushwriter= In graph mode, it would have been impossible to perform these API...

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 =...

Segfault and OOB write due to incomplete validation in `EditDistance` in TensorFlow

ImpactThe implementation of tf.rawops.EditDistance has incomplete validation. Users can pass negative values to cause a segmentation fault based denial of service:pythonimport tensorflow as tfhypothesisindices = tf.constant-1250999896764, shape=3, 3, dtype=tf.int64 hypothesisvalues = tf.constant0...

Denial of service in `tf.ragged.constant` due to lack of validation

ImpactThe implementation of tf.ragged.constant does not fully validate the input arguments. This results in a denial of service by consuming all available memory:pythonimport tensorflow as tftf.ragged.constantpylist=,raggedrank=8968073515812833920 PatchesWe have patched the issue in GitHub commit...

Missing validation results in undefined behavior in `QuantizedConv2D`

ImpactThe implementation of tf.rawops.QuantizedConv2D does not fully validate the input arguments:pythonimport tensorflow as tfinput = tf.constant1, shape=1, 2, 3, 3, dtype=tf.quint8filter = tf.constant1, shape=1, 2, 3, 3, dtype=tf.quint8 bad argsmininput = tf.constant, shape=0,...

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...

Integer overflow in `SpaceToBatchND`

ImpactThe implementation of tf.rawops.SpaceToBatchND in all backends such as XLA and handwritten kernels is vulnerable to an integer overflow:pythonimport tensorflow as tfinput = tf.constant-3.5e+35, shape=10,19,22, dtype=tf.float32blockshape = tf.constant-1879048192, shape=2,...

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 =...

Segfault due to missing support for quantized types

ImpactThere is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1. ops which don't yet have support for quantized types added after migration to TF 2.x:pythonimport numpy as npimport tensorflow as...

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...

Integer overflow in `SpaceToBatchND`

ImpactThe implementation of tf.rawops.SpaceToBatchND in all backends such as XLA and handwritten kernels is vulnerable to an integer overflow:pythonimport tensorflow as tfinput = tf.constant-3.5e+35, shape=10,19,22, dtype=tf.float32blockshape = tf.constant-1879048192, shape=2,...

Segfault due to missing support for quantized types

ImpactThere is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1. ops which don't yet have support for quantized types added after migration to TF 2.x:pythonimport numpy as npimport tensorflow as...

Missing validation results in undefined behavior in `QuantizedConv2D`

ImpactThe implementation of tf.rawops.QuantizedConv2D does not fully validate the input arguments:pythonimport tensorflow as tfinput = tf.constant1, shape=1, 2, 3, 3, dtype=tf.quint8filter = tf.constant1, shape=1, 2, 3, 3, dtype=tf.quint8 bad argsmininput = tf.constant, shape=0,...

Denial of service in `tf.ragged.constant` due to lack of validation

ImpactThe implementation of tf.ragged.constant does not fully validate the input arguments. This results in a denial of service by consuming all available memory:pythonimport tensorflow as tftf.ragged.constantpylist=,raggedrank=8968073515812833920 PatchesWe have patched the issue in GitHub commit...

Missing validation causes denial of service via `LoadAndRemapMatrix`

ImpactThe implementation of tf.rawops.LoadAndRemapMatrix 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 tfckptpath = tf.constant "/tmp/warmstartingutiltest5kl2a3pc/tmpph76tep2/model-0"...

Missing validation causes denial of service via `Conv3DBackpropFilterV2`

ImpactThe implementation of tf.rawops.Conv3DBackpropFilterV2 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.rawops.Conv3DBackpropFilterV2 input=tf.constant.5053710941,...

Missing validation causes denial of service via `Conv3DBackpropFilterV2`

ImpactThe implementation of tf.rawops.Conv3DBackpropFilterV2 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.rawops.Conv3DBackpropFilterV2 input=tf.constant.5053710941,...

Missing validation causes denial of service via `LSTMBlockCell`

ImpactThe implementation of tf.rawops.LSTMBlockCell 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.rawops.LSTMBlockCell x=tf.constant0.837607, shape=28,29, dtype=tf.float32,...

Missing validation causes denial of service via `LoadAndRemapMatrix`

ImpactThe implementation of tf.rawops.LoadAndRemapMatrix 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 tfckptpath = tf.constant "/tmp/warmstartingutiltest5kl2a3pc/tmpph76tep2/model-0"...

Missing validation causes denial of service via `UnsortedSegmentJoin`

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.rawops.UnsortedSegmentJoin inputs=tf.constant"this", shape=12,...

Missing validation causes denial of service via `UnsortedSegmentJoin`

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.rawops.UnsortedSegmentJoin inputs=tf.constant"this", shape=12,...

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 denial of service via `StagePeek`

ImpactThe implementation of tf.rawops.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:pythonimport tensorflow as tfindex = tf.constant, shape=0, dtype=tf.int32tf.rawops.StagePeekindex=index,...