CVSS: 7.1EPSS: 0%CPEs: 4EXPL: 1CVE-2021-29582 – Heap OOB read in `tf.raw_ops.Dequantize`
https://notcve.org/view.php?id=CVE-2021-29582
TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.Dequantize`, an attacker can trigger a read from outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/26003593aa94b1742f34dc22ce88a1e17776a67d/tensorflow/core/kernels/dequantize_op.cc#L106-L131) accesses the `min_range` and `max_range` tensors in parallel but fails to check that they have the same shape. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. • https://github.com/tensorflow/tensorflow/commit/5899741d0421391ca878da47907b1452f06aaf1b https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c45w-2wxr-pp53 • CWE-125: Out-of-bounds Read •
CVSS: 7.8EPSS: 0%CPEs: 4EXPL: 1CVE-2021-29583 – Heap buffer overflow and undefined behavior in `FusedBatchNorm`
https://notcve.org/view.php?id=CVE-2021-29583
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FusedBatchNorm` is vulnerable to a heap buffer overflow. If the tensors are empty, the same implementation can trigger undefined behavior by dereferencing null pointers. The implementation(https://github.com/tensorflow/tensorflow/blob/57d86e0db5d1365f19adcce848dfc1bf89fdd4c7/tensorflow/core/kernels/fused_batch_norm_op.cc) fails to validate that `scale`, `offset`, `mean` and `variance` (the last two only when required) all have the same number of elements as the number of channels of `x`. This results in heap out of bounds reads when the buffers backing these tensors are indexed past their boundary. • https://github.com/tensorflow/tensorflow/commit/6972f9dfe325636b3db4e0bc517ee22a159365c0 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9xh4-23q4-v6wr • CWE-125: Out-of-bounds Read CWE-476: NULL Pointer Dereference •
CVSS: 5.5EPSS: 0%CPEs: 4EXPL: 1CVE-2021-29584 – CHECK-fail due to integer overflow
https://notcve.org/view.php?id=CVE-2021-29584
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in caused by an integer overflow in constructing a new tensor shape. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/0908c2f2397c099338b901b067f6495a5b96760b/tensorflow/core/kernels/sparse_split_op.cc#L66-L70) builds a dense shape without checking that the dimensions would not result in overflow. The `TensorShape` constructor(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when `InitDims`(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status. This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows. • https://github.com/tensorflow/tensorflow/commit/4c0ee937c0f61c4fc5f5d32d9bb4c67428012a60 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xvjm-fvxx-q3hv • CWE-190: Integer Overflow or Wraparound •
CVSS: 7.8EPSS: 0%CPEs: 4EXPL: 1CVE-2021-29525 – Division by 0 in `Conv2DBackpropInput`
https://notcve.org/view.php?id=CVE-2021-29525
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.Conv2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/b40060c9f697b044e3107917c797ba052f4506ab/tensorflow/core/kernels/conv_grad_input_ops.h#L625-L655) does a division by a quantity that is controlled by the caller. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. • https://github.com/tensorflow/tensorflow/commit/2be2cdf3a123e231b16f766aa0e27d56b4606535 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xm2v-8rrw-w9pm • CWE-369: Divide By Zero •
CVSS: 5.5EPSS: 0%CPEs: 4EXPL: 1CVE-2021-29526 – Division by 0 in `Conv2D`
https://notcve.org/view.php?id=CVE-2021-29526
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.Conv2D`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/988087bd83f144af14087fe4fecee2d250d93737/tensorflow/core/kernels/conv_ops.cc#L261-L263) does a division by a quantity that is controlled by the caller. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. • https://github.com/tensorflow/tensorflow/commit/b12aa1d44352de21d1a6faaf04172d8c2508b42b https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4vf2-4xcg-65cx • CWE-369: Divide By Zero •