GHSA-977j-xj7q-2jr9

    Dashboard / Vulnerabilities / GHSA-977j-xj7q-2jr9

    GHSA-977j-xj7q-2jr9

    Published: 28 Jan 2020Last Modified: 10 Sept 2026

    Summary: Segmentation faultin TensorFlow when converting a Python string to `tf.float16`

    Details: ### Impact 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. ### Patches We have patched the vulnerability in GitHub commit [5ac1b9](https://github.com/tensorflow/tensorflow/commit/5ac1b9e24ff6afc465756edf845d2e9660bd34bf). We are additionally releasing 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. We encourage users to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0. ### For more information Please consult [`SECURITY.md`](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.

    Affected packages

    Package

    Name: tensorflow

    Purl: pkg:pypi/tensorflow

    Affected ranges

    Type: ECOSYSTEM

    Events:

    Introduced- 0
    Fixed -1.15.2

    Affected versions

    0.12.0
    0.12.1

    Common Vulnerability Scoring System

    Attack Vector
    Network
    Adjacent
    Local
    Physical
    Privileges Required
    None
    Low
    High
    User Interaction
    None
    Required
    Scope
    Unchanged
    Changed
    Confidentiality
    None
    Low
    High
    Integrity
    None
    Low
    High
    Availability
    None
    Low
    High