Reachable Assertion in Tensorflow

Impact When decoding a tensor from protobuf, a TensorFlow process can encounter cases where a CHECK assertion is invalidated based on user controlled arguments, if the tensors have an invalid dtype and 0 elements or an invalid shape. This allows attackers to cause denial of services in TensorFlow...

Crash when type cannot be specialized in Tensorflow

Impact Under certain scenarios, TensorFlow can fail to specialize a type during shape inference: cc void InferenceContext::PreInputInit const OpDef& opdef, const std::vector& inputtensors, const std::vector& inputtensorsasshapes const auto ret = fulltype::SpecializeTypeattrs, opdef;...

`CHECK`-fails due to attempting to build a reference tensor

Impact A malicious user can cause a denial of service by altering a SavedModel such that Grappler optimizer would attempt to build a tensor using a reference dtype. This would result in a crash due to a CHECK-fail in the Tensor constructor as reference types are not allowed. Patches We have patch...

Integer overflow in TensorFlow

Impact Under certain scenarios, Grappler component of TensorFlow is vulnerable to an integer overflow during cost estimation for crop and resize. Since the cropping parameters are user controlled, a malicious person can trigger undefined behavior. Patches We have patched the issue in GitHub commi...

GHSA-43JF-985Q-588J Multiple `CHECK`-fails in `function.cc` in TensowFlow

Impact A malicious user can cause a denial of service by altering a SavedModel such that assertions in function.cc would be falsified and crash the Python interpreter. Patches We have patched the issue in GitHub commits dcc21c7bc972b10b6fb95c2fb0f4ab5a59680ec2 and...

Multiple `CHECK`-fails in `function.cc` in TensowFlow

Impact A malicious user can cause a denial of service by altering a SavedModel such that assertions in function.cc would be falsified and crash the Python interpreter. Patches We have patched the issue in GitHub commits dcc21c7bc972b10b6fb95c2fb0f4ab5a59680ec2 and...

Memory leak in decoding PNG images

Impact When decoding PNG images TensorFlow can produce a memory leak if the image is invalid. After calling png::CommonInitDecode..., &decode, the decode value contains allocated buffers which can only be freed by calling png::CommonFreeDecode&decode. However, several error case in the function...

Out of bounds read and write in Tensorflow

Impact There is a typo in TensorFlow's SpecializeType which results in heap OOB read/write: cc for int i = 0; i argssize; j++ auto arg = t-mutableargsi; // ... Due to a typo, arg is initialized to the ith mutable argument in a loop where the loop index is j. Hence it is possible to assign to arg...

Integer overflow in Tensorflow

Impact The implementation of shape inference for Dequantize is vulnerable to an integer overflow weakness: python import tensorflow as tf input = tf.constant1,1,dtype=tf.qint32 @tf.function def test: y = tf.rawops.Dequantize input=input, minrange=1.0, maxrange=10.0, mode='MINCOMBINED',...

Out of bounds read in Tensorflow

Impact The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses: python import tensorflow as tf @tf.function def test: y = tf.rawops.Dequantize input=tf.constant1,1,dtype=tf.qint32, minrange=1.0, maxrange=10.0, mode='MINCOMBINED',...

Abort caused by allocating a vector that is too large in Tensorflow

Impact During shape inference, TensorFlow can allocate a large vector based on a value from a tensor controlled by the user: cc const auto numdims = Valueshapedim; std::vector dims; dims.reservenumdims; Patches We have patched the issue in GitHub commit 1361fb7e29449629e1df94d44e0427ebec8c83c7. T...

`CHECK`-failures during Grappler's `IsSimplifiableReshape` in Tensorflow

Impact The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a SavedModel such that IsSimplifiableReshape would trigger CHECK failures. Patches We have patched the issue in GitHub commits ebc1a2ffe5a7573d905e99bd0ee3568ee07c12c1,...

Crash in `tf.math.segment_*` operations

Impact The implementation of tf.math.segment operations results in a CHECK-fail related abort and denial of service if a segment id in segmentids is large. python import tensorflow as tf tf.math.segmentmaxdata=np.ones1,10,1, segmentids=1676240524292489355 tf.math.segmentmindata=np.ones1,10,1,...

Crash in `max_pool3d` when size argument is 0 or negative

Impact The Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative: python import tensorflow as tf poolsize = 2, 2, 0 layer = tf.keras.layers.MaxPooling3Dstrides=1, poolsize=poolsize inputtensor = tf.random.uniform3, 4, 10, 11, 12, dtype=tf.float32 r...

Overflow/crash in `tf.tile` when tiling tensor is large

Impact If tf.tile is called with a large input argument then the TensorFlow process will crash due to a CHECK-failure caused by an overflow. python import tensorflow as tf import numpy as np tf.keras.backend.tilex=np.ones1,1,1, n=100000000,100000000, 100000000 The number of elements in the output...

Overflow/crash in `tf.image.resize` when size is large

Impact If tf.image.resize is called with a large input argument then the TensorFlow process will crash due to a CHECK-failure caused by an overflow. python import tensorflow as tf import numpy as np tf.keras.layers.UpSampling2D size=1610637938, dataformat='channelsfirst',...

Incomplete validation in `tf.summary.create_file_writer`

Impact If tf.summary.createfilewriter is called with non-scalar arguments code crashes due to a CHECK-fail. python import tensorflow as tf import numpy as np tf.summary.createfilewriterlogdir='', flushmillis=np.ones1,2 Patches We have patched the issue in GitHub commit...

Overflow/crash in `tf.range`

Impact While calculating the size of the output within the tf.range kernel, there is a conditional statement of type int64 = condition ? int64 : double. Due to C++ implicit conversion rules, both branches of the condition will be cast to double and the result would be truncated before the...

GHSA-XRQM-FPGR-6HHX Overflow/crash in `tf.range`

Impact While calculating the size of the output within the tf.range kernel, there is a conditional statement of type int64 = condition ? int64 : double. Due to C++ implicit conversion rules, both branches of the condition will be cast to double and the result would be truncated before the...

Missing validation during checkpoint loading

Impact An attacker can trigger undefined behavior, integer overflows, segfaults and CHECK-fail crashes if they can change saved checkpoints from outside of TensorFlow. This is because the checkpoints loading infrastructure is missing validation for invalid file formats. Patches We have patched th...