CVE-2020-5215: Segmentation faultin TensorFlow when converting a Python string to tf.float16

Severity: high (CVSS 7.5 v3.1)
Exploited in the wild: not listed in CISA KEV
EPSS: 0.6% probability of exploitation in the next 30 days
Public exploit or detection template: yes
Published: 2020-01-28 · updated 2026-06-17
Weakness: CWE-754

Description

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: before 1.15.2; from 2.0.0 before 2.0.1 — fixed in 1.15.2, 2.0.1

How to fix

Upgrade to a fixed version: tensorflow 1.15.2, 2.0.1. Check the vendor advisory for mitigations.

References

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