Memory leak 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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Configuration 1 [-]
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Configuration 2 [-]
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No data available yet.
| Source | ID | Title |
|---|---|---|
EUVD |
EUVD-2020-0188 | In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes a list of strings to `dlpack.to_dlpack` there is a memory leak following an expected validation failure. The issue occurs because the `status` argument during validation failures is not properly checked. Since each of the above methods can return an error status, the `status` value must be checked before continuing. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1. |
Github GHSA |
GHSA-8fxw-76px-3rxv | Memory leak in Tensorflow |
No CVSS v4.0
No CVSS v3.0
This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.834% probability within 30 days)
Key SSVC decision points have not yet been added.
No history.