Segfault in TensorFlow if `tf.histogram_fixed_width` is called with NaN values
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 available yet.
| Source | ID | Title |
|---|---|---|
EUVD |
EUVD-2022-5854 | 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, the implementation of `tf.histogram_fixed_width` is vulnerable to a crash when the values array contain `Not a Number` (`NaN`) elements. The implementation assumes that all floating point operations are defined and then converts a floating point result to an integer index. If `values` contains `NaN` then the result of the division is still `NaN` and the cast to `int32` would result in a crash. This only occurs on the CPU implementation. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue. |
Github GHSA |
GHSA-xrp2-fhq4-4q3w | Segfault if `tf.histogram_fixed_width` is called with NaN values in TensorFlow |
No CVSS v4.0
No CVSS v3.0
This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.321% probability within 30 days)
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