Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. The vulnerability exists due to division by zero error in tf.rawops.MaxPoolGradWithArgmax which is caused by the failure to validate the batch dimension of the tensor is non-zero before dividing it...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. An attacker is able to exploit the vulnerability by calling tf.rawops.ImmutableConst with a dtype of tf.resource or tf.variant resulting in a segfault...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. The vulnerability exists due to an undefined behavior in tf.rawops.MaxPool3DGradGrad by dereferencing null pointers backing attacker-supplied empty tensors...

Out-of-Bounds Read

tensorflow has out-of-bound read. The vulnerability exists due to failure to validate the indices used to access elements of input/output arrays...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. The vulnerability exists due to MatrixTriangularSolve failing to terminate kernel execution if one validation condition fails...

Out-of-Bounds Read

tensorflow has out-of-bound read. The vulnerability exists due to the lack of validation of axis allowing an attacker to be able to read data from outside of the bounds of heap allocated in the buffer in tf.rawops.QuantizeAndDequantizeV3...

Out-of-Bounds Read

tensorflow has out-of-bound read. The vulnerability exists due to a lack of validation in tf.rawops.Dequantize which allows an attacker to trigger a read from outside the allocated bounds of heap...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. An attacker may exploit the vulnerability by passing invalid arguments to tf.rawops.Dilation2DBackpropInput causing an out of bounds write to the heap...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. An attacker may exploit the vulnerability by inputting a crafted x tensor which may cause a FPE runtime error in tf.rawops.FusedBatchNorm...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. An attacker is able to send a malicious input to cause a memory overflow in ParseAttrValue from nested tensors...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. An attacker is able to exploit the vulnerability by inputting a crafted model such that the numsplits would be 0, into the split TFLite operator...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. A heap underflow occurs because invalid values for axis argument are accepted in tf.rawops.QuantizeAndDequantizeV2, allowing an attacker to read/write to other data on the heap...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. An integer division by zero undefined behavior occurs because it performs division without checking not zero in TFLite computation for size of output after TFLite padding, allowing an attacker to crash the application...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. A stack overflow in tf.rawops.ReverseSequence occurs because it fails to validate that seqdim and batchdim arguments are valid...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. An attacker is able to send a malicious input to cause null pointer dereference in TrySimplify, crashing the application...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. A heap buffer overflow occurs in tf.rawops.MaxPool3DGradGrad as it fails to check that the initialization of Pool3dParameters completes successfully...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. A division by zero undefined behavior in 'tf.rawops.Conv2DBackpropFilter occurs because it performs division without checking not zero, allowing an attacker to crash the application...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. A heap buffer overflow occurs because the splits argument of RaggedBincount does not specify a valid SparseTensor...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. A division by zero undefined behavior in Conv3D occurs because it performs a modulo operation based on user controlled input, allowing an attacker to crash the application...

Denial Of Service (DoS)

tensorflow is vulnerable to denial of service. An attacker is able to send a malicious input to cause buffer overflows due to CHECK-fail in tf.rawops.AddManySparseToTensorsMap...