CVE-2021-37651
Summary
| CVE | CVE-2021-37651 |
| State | PUBLIC |
| Assigner | [email protected] |
| Source Priority | CVE Program / NVD first with legacy fallback |
| Published | 2021-08-12 21:15:00 UTC |
| Updated | 2021-08-18 14:46:00 UTC |
| Description | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. |
NVD Known Affected Configurations (CPE 2.3)
References
| Reference | Source | Link | Tags |
|---|
| Heap buffer overflow in `FractionalAvgPoolGrad` · Advisory · tensorflow/tensorflow · GitHub |
CONFIRM |
github.com |
|
| Validate dimensions of input tensor in `FractionalAvgPoolGrad` · tensorflow/tensorflow@0f93175 · GitHub |
MISC |
github.com |
|
| CVE Program record |
CVE.ORG |
www.cve.org |
canonical |
| NVD vulnerability detail |
NVD |
nvd.nist.gov |
canonical, analysis |
No vendor comments have been submitted for this CVE.
Legacy QID Mappings
- 981520 Python (pip) Security Update for tensorflow-gpu (GHSA-hpv4-7p9c-mvfr)