Upstream information
Description
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. If the tensors are empty, the validation mentioned in the above paragraph would also trigger and prevent the undefined behavior. 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.SUSE information
Overall state of this security issue: Does not affect SUSE products
This issue is currently rated as having important severity.
| National Vulnerability Database | |
|---|---|
| Base Score | 4.6 |
| Vector | AV:L/AC:L/Au:N/C:P/I:P/A:P |
| Access Vector | Local |
| Access Complexity | Low |
| Authentication | None |
| Confidentiality Impact | Partial |
| Integrity Impact | Partial |
| Availability Impact | Partial |
| National Vulnerability Database | |
|---|---|
| Base Score | 7.8 |
| Vector | CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H |
| Attack Vector | Local |
| Attack Complexity | Low |
| Privileges Required | Low |
| User Interaction | None |
| Scope | Unchanged |
| Confidentiality Impact | High |
| Integrity Impact | High |
| Availability Impact | High |
| CVSSv3 Version | 3.1 |
SUSE Timeline for this CVE
CVE page created: Mon May 17 08:58:28 2021CVE page last modified: Sat Mar 30 16:29:57 2024