Heap buffer overflow in Tensorflow
Default status is the baseline for the product, each version can override it (e.g. patched versions marked unaffected).
| Vendor | Product | Default status | Versions | ||||||
|---|---|---|---|---|---|---|---|---|---|
| tensorflow | tensorflow | affected |
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| 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 |
No CVSS v4.0
No CVSS v3.0
This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.542% probability within 30 days)
Key SSVC decision points have not yet been added.
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