Vulnerability identifier: #VU30396

Vulnerability risk: Medium

CVSSv3.1: 6.5 [CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H/E:U/RL:O/RC:C]

CVE-ID: CVE-2020-5215

CWE-ID: CWE-20

Exploitation vector: Network

Exploit availability: No

Vulnerable software:
TensorFlow
Server applications / Other server solutions

Vendor: TensorFlow

Description

The vulnerability allows a remote non-authenticated attacker to perform a denial of service (DoS) attack.

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.

Mitigation
Install update from vendor's website.

Vulnerable software versions

TensorFlow: 2.0.0

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External links
http://github.com/tensorflow/tensorflow/commit/5ac1b9e24ff6afc465756edf845d2e9660bd34bf
http://github.com/tensorflow/tensorflow/releases/tag/v1.15.2
http://github.com/tensorflow/tensorflow/releases/tag/v2.0.1
http://github.com/tensorflow/tensorflow/security/advisories/GHSA-977j-xj7q-2jr9

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Q & A

Can this vulnerability be exploited remotely?

Yes. This vulnerability can be exploited by a remote non-authenticated attacker via the Internet.

Is there known malware, which exploits this vulnerability?

No. We are not aware of malware exploiting this vulnerability.