CVE-2020-5215
Published: Jan 28, 2020
Modified: Aug 4, 2024
CVSS v3.1
5.0
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.
| Vendor | Product | Versions |
|---|---|---|
TensorFlow | TensorFlow | affected < 1.15.2affected = 2.0.0 |
Weaknesses (CWE)
CVSS v3.1 Details
CVSS v3.1 Vector
CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:C/C:L/I:L/A:L
Attack Vector
Attack Complexity
Privileges Required
User Interaction
Scope
Confidentiality
Integrity
Availability
References
Security Training
Train your team to recognize and prevent security threats with our comprehensive security awareness program.
Start TrainingVulnerability Scanning
Discover vulnerabilities in your applications and infrastructure before attackers do.
Scan Now