CVE-2020-5215
In TensorFlow before 1.15.2 and 2.0.1, converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value. Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions. This can be easily reproduced by tf.constant("hello", tf.float16), if eager execution is enabled. This issue is patched in TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched. TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected. Users are encouraged to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.
EPSS 0.23% · 46.2th percentile
Risk Scores
Affected Products
| Vendor | Product | Versions |
|---|---|---|
| Bitnami | tensorflow | 2.0.0, 0 |
| Bitnami | tensorflow | 0, 2.0.0 |
Timeline
- Jan 28, 2020 CVE Published
- Apr 14, 2021 EPSS Score
- Jun 23, 2021 EPSS Score
- Aug 24, 2021 EPSS Score
- Oct 26, 2021 EPSS Score
- Jan 6, 2022 EPSS Score
- Feb 4, 2022 EPSS Score
- Feb 28, 2022 EPSS Score
- Apr 1, 2022 EPSS Score
- May 1, 2022 EPSS Score
- Jul 3, 2022 EPSS Score
- Sep 4, 2022 EPSS Score
References
- https://github.com/tensorflow/tensorflow/commit/5ac1b9e24ff6afc465756edf845d2e9660bd34bf url
- https://github.com/tensorflow/tensorflow/releases/tag/v1.15.2 url
- https://github.com/tensorflow/tensorflow/releases/tag/v2.0.1 url
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-977j-xj7q-2jr9 url
- https://nvd.nist.gov/vuln/detail/CVE-2020-5215 url