Memory exhaustion in Tensorflow
Default status is the baseline for the product, each version can override it (e.g. patched versions marked unaffected).
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Configuration 1 [-]
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| Source | ID | Title |
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EUVD |
EUVD-2022-0295 | Tensorflow is an Open Source Machine Learning Framework. The implementation of `ThreadPoolHandle` can be used to trigger a denial of service attack by allocating too much memory. This is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. |
Github GHSA |
GHSA-c582-c96p-r5cq | Memory exhaustion in Tensorflow |
No CVSS v4.0
No CVSS v3.0
This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.765% probability within 30 days)
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