In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Metrics
Affected Vendors & Products
Advisories
| Source | ID | Title |
|---|---|---|
EUVD |
EUVD-2020-0194 | In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. |
Github GHSA |
GHSA-jc87-6vpp-7ff3 | Heap buffer overflow in Tensorflow |
Fixes
Solution
No solution given by the vendor.
Workaround
No workaround given by the vendor.
References
History
No history.
Status: PUBLISHED
Assigner: GitHub_M
Published:
Updated: 2024-08-04T13:08:22.711Z
Reserved: 2020-06-25T00:00:00
Link: CVE-2020-15198
No data.
Status : Modified
Published: 2020-09-25T19:15:15.057
Modified: 2024-11-21T05:05:03.877
Link: CVE-2020-15198
No data.
OpenCVE Enrichment
No data.
EUVD
Github GHSA