CVSS: 5.5EPSS: 0%CPEs: 4EXPL: 1CVE-2021-29580 – Undefined behavior and `CHECK`-fail in `FractionalMaxPoolGrad`
https://notcve.org/view.php?id=CVE-2021-29580
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a `CHECK` condition becomes false and aborts the process. The implementation(https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues. • https://github.com/tensorflow/tensorflow/commit/32fdcbff9d06d010d908fcc4bd4b36eb3ce15925 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgp • CWE-908: Use of Uninitialized Resource •
CVSS: 5.5EPSS: 0%CPEs: 4EXPL: 1CVE-2021-29581 – Segfault in `CTCBeamSearchDecoder`
https://notcve.org/view.php?id=CVE-2021-29581
TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.CTCBeamSearchDecoder`, an attacker can trigger denial of service via segmentation faults. The implementation(https://github.com/tensorflow/tensorflow/blob/a74768f8e4efbda4def9f16ee7e13cf3922ac5f7/tensorflow/core/kernels/ctc_decoder_ops.cc#L68-L79) fails to detect cases when the input tensor is empty and proceeds to read data from a null buffer. 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/b1b323042264740c398140da32e93fb9c2c9f33e https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vq2r-5xvm-3hc3 • CWE-908: Use of Uninitialized Resource •
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 •