Segfault due to missing support for quantized types 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 | |||||||||||||||
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| tensorflow | tensorflow | affected |
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Configuration 1 [-]
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No data.
No data available yet.
| Source | ID | Title |
|---|---|---|
EUVD |
EUVD-2022-2494 | TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, there is a potential for segfault / denial of service in TensorFlow by calling `tf.compat.v1.*` ops which don't yet have support for quantized types, which was added after migration to TensorFlow 2.x. In these scenarios, since the kernel is missing, a `nullptr` value is passed to `ParseDimensionValue` for the `py_value` argument. Then, this is dereferenced, resulting in segfault. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue. |
Github GHSA |
GHSA-54ch-gjq5-4976 | Segfault due to missing support for quantized types |
No CVSS v4.0
No CVSS v3.0
This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.325% probability within 30 days)
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