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CVE-2020-5215

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Date: February 5, 2020

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.

Language: Python

Severity Score

Severity Score

Weakness Type (CWE)

Input Validation

CWE-20

Top Fix

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Upgrade Version

Upgrade to version tensorflow - 1.15.2,2.0.1;tensorflow-cpu - 1.15.2,2.0.1;tensorflow-gpu - 1.15.2,2.0.1

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CVSS v3.1

Base Score:
Attack Vector (AV): NETWORK
Attack Complexity (AC): LOW
Privileges Required (PR): NONE
User Interaction (UI): NONE
Scope (S): UNCHANGED
Confidentiality (C): NONE
Integrity (I): NONE
Availability (A): HIGH

CVSS v2

Base Score:
Access Vector (AV): NETWORK
Access Complexity (AC): MEDIUM
Authentication (AU): NONE
Confidentiality (C): NONE
Integrity (I): NONE
Availability (A): PARTIAL
Additional information:

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