555 matches found
`FractionalMaxPoolGrad` Heap out of bounds read
Impact If FractionMaxPoolGrad is given outsize inputs rowpoolingsequence and colpoolingsequence, TensorFlow will crash. python import tensorflow as tf tf.rawops.FractionMaxPoolGrad originput = 1, 1, 1, 1, 1, origoutput = 1, 1, 1, outbackprop = 3, 3, 6, rowpoolingsequence = -0x4000000, 1, 1,...
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,...
`CHECK` fail in `BCast` overflow
Impact If 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. python import tensorflow as tf value = tf.constantshape=2, 1024, 1024, 1024...
Segfault via invalid attributes in `pywrap_tfe_src.cc`
Impact If a list of quantized tensors is assigned to an attribute, the pywrap code fails to parse the tensor and returns a nullptr, which is not caught. An example can be seen in tf.compat.v1.extractvolumepatches by passing in quantized tensors as input ksizes. python import numpy as np import...
Overflow in `FusedResizeAndPadConv2D`
Impact When tf.rawops.FusedResizeAndPadConv2D is given a large tensor shape, it overflows. python import tensorflow as tf mode = "REFLECT" strides = 1, 1, 1, 1 padding = "SAME" resizealigncorners = False input = tf.constant147, shape=3,3,1,1, dtype=tf.float16 size =...
GHSA-W58W-79XV-6VCJ Out of bounds segmentation fault due to unequal op inputs in Tensorflow
Impact tf.rawops.DynamicStitch specifies input sizes when it is registered. cpp REGISTEROP"DynamicStitch" .Input"indices: N int32" .Input"data: N T" .Output"merged: T" .Attr"N : int = 1" .Attr"T : type" .SetShapeFnDynamicStitchShapeFunction; When it receives a differing number of inputs, such as...
scap-security-guide bug fix and enhancement update
An update is available for scap-security-guide. This update affects Rocky Linux 9. A Common Vulnerability Scoring System CVSS base score, which gives a detailed severity rating, is available for each vulnerability from the CVE list For detailed information on changes in this release, see the Rock...
scap-security-guide bug fix and enhancement update
An update is available for scap-security-guide. This update affects Rocky Linux 8. A Common Vulnerability Scoring System CVSS base score, which gives a detailed severity rating, is available for each vulnerability from the CVE list For detailed information on changes in this release, see the Rock...
TensorFlow vulnerable to heap out of bounds read in filesystem glob matching
Impact The general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories: cc if !fs-Matchchildpath, dirsdirindex ... Since dirindex is unconditionaly incremented outside of the lambda function where the...
GHSA-9JJW-HF72-3MXW TensorFlow vulnerable to heap out of bounds read in filesystem glob matching
Impact The general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories: cc if !fs-Matchchildpath, dirsdirindex ... Since dirindex is unconditionaly incremented outside of the lambda function where the...
TensorFlow vulnerable to `CHECK` fail in `Save` and `SaveSlices`
Impact If Save or SaveSlices is run over tensors of an unsupported dtype, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf filename = tf.constant"" tensornames = tf.constant"" Save data = tf.casttf.random.uniformshape=1,...
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,...
TensorFlow vulnerable to `CHECK` fail in `LRNGrad`
Impact If 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. python import tensorflow as tf depthradius = 1 bias = 1.59018219 alpha = 0.117728651 beta = 0.404427052 inputgrads = tf.random.uniformshape=4,...
TensorFlow vulnerable to segfault in `RaggedBincount`
Impact If RaggedBincount is given an empty input tensor splits, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf binaryoutput = True splits = tf.random.uniformshape=0, minval=-10000, maxval=10000, dtype=tf.int64, seed=-7430 values =...
TensorFlow vulnerable to `CHECK` fail in `tf.linalg.matrix_rank`
Impact When 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. python import tensorflow as tf a = tf.constant, shape=0, 1, 1, dtype=tf.float32 tf.linalg.matrixranka=a Patches We have patched the issue in GitHub...
TensorFlow vulnerable to `CHECK` fail in `MaxPool`
Impact When 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. python import tensorflow as tf import numpy as np input = np.ones1, 1, 1, 1 ksize = 1, 1, 2, ...
TensorFlow vulnerable to `CHECK` fail in `FractionalMaxPoolGrad`
Impact FractionalMaxPoolGrad 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: python import tensorflow as tf overlapping = True originput = tf.constant.453409232,...
TensorFlow vulnerable to segfault in `QuantizedRelu` and `QuantizedRelu6`
Impact If 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. python import tensorflow as tf outtype = tf.quint8 features = tf.constant28, shape=4,2, dtype=tf.quint8 minfeatures...
TensorFlow vulnerable to segfault in `QuantizeDownAndShrinkRange`
Impact If 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. python import tensorflow as tf outtype = tf.quint8 input = tf.constant1, shape=3, dtype=tf.qint32 inputmin = tf.constant,...
TensorFlow vulnerable to segfault in `QuantizedMatMul`
Impact If QuantizedMatMul is given nonscalar input for: - mina - maxa - minb - maxb It gives a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf Toutput = tf.qint32 transposea = False transposeb = False Tactivation = tf.quint8 a = tf.constant7,...