CVE-2020-5215
Apache TensorFlow Eager String to Float16 Denial of Service Vulnerability
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.
INFO
Published Date :
Jan. 28, 2020, 10:15 p.m.
Last Modified :
Feb. 5, 2020, 9:02 p.m.
Source :
[email protected]
Remotely Exploitable :
Yes !
Impact Score :
3.6
Exploitability Score :
3.9
References to Advisories, Solutions, and Tools
Here, you will find a curated list of external links that provide in-depth
information, practical solutions, and valuable tools related to
CVE-2020-5215
.
URL | Resource |
---|---|
https://github.com/tensorflow/tensorflow/commit/5ac1b9e24ff6afc465756edf845d2e9660bd34bf | Patch |
https://github.com/tensorflow/tensorflow/releases/tag/v1.15.2 | Release Notes |
https://github.com/tensorflow/tensorflow/releases/tag/v2.0.1 | Release Notes |
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-977j-xj7q-2jr9 | Exploit Patch Third Party Advisory |
We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).
Results are limited to the first 15 repositories due to potential performance issues.
The following list is the news that have been mention
CVE-2020-5215
vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2020-5215
vulnerability over time.
Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.
-
CVE Modified by [email protected]
May. 14, 2024
Action Type Old Value New Value -
Initial Analysis by [email protected]
Feb. 05, 2020
Action Type Old Value New Value Added CVSS V2 NIST (AV:N/AC:M/Au:N/C:N/I:N/A:P) Added CVSS V3.1 NIST AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H Changed Reference Type https://github.com/tensorflow/tensorflow/commit/5ac1b9e24ff6afc465756edf845d2e9660bd34bf No Types Assigned https://github.com/tensorflow/tensorflow/commit/5ac1b9e24ff6afc465756edf845d2e9660bd34bf Patch Changed Reference Type https://github.com/tensorflow/tensorflow/releases/tag/v1.15.2 No Types Assigned https://github.com/tensorflow/tensorflow/releases/tag/v1.15.2 Release Notes Changed Reference Type https://github.com/tensorflow/tensorflow/releases/tag/v2.0.1 No Types Assigned https://github.com/tensorflow/tensorflow/releases/tag/v2.0.1 Release Notes Changed Reference Type https://github.com/tensorflow/tensorflow/security/advisories/GHSA-977j-xj7q-2jr9 No Types Assigned https://github.com/tensorflow/tensorflow/security/advisories/GHSA-977j-xj7q-2jr9 Exploit, Patch, Third Party Advisory Added CWE NIST CWE-20 Added CPE Configuration OR *cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* versions up to (excluding) 1.15.2 *cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* versions from (including) 2.0.0 up to (excluding) 2.0.1
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2020-5215
is
associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification
(CAPEC)
stores attack patterns, which are descriptions of the common attributes and
approaches employed by adversaries to exploit the CVE-2020-5215
weaknesses.
Exploit Prediction
EPSS is a daily estimate of the probability of exploitation activity being observed over the next 30 days.
0.36 }} 0.11%
score
0.72301
percentile