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.
- Affected products
- Tensorflow
- Google Tensorflow
- < 1.15.2, 2.0.1
- Fix
- Available
- CVSS 3.1
- 7.5 HIGH
- EPSS
- 0.6% (45th percentile)
- Weakness
- CWE-754, CWE-20
- NVD status
- Modified
- Published
- 2020-01-28
No indexed exploits for CVE-2020-5215 yet
Our index is partial: it proves presence, never absence
No exploit for CVE-2020-5215 has been indexed yet. Our index is built from live traffic and upstream syncs, so this page can only say what it knows — not that no exploit exists.