CVE-2022-35990
TensorFlow Fake Quantization DoS Vulnerability
Description
TensorFlow is an open source platform for machine learning. When `tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient` receives input `min` or `max` of rank other than 1, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.There are no known workarounds for this issue.
INFO
Published Date :
Sept. 16, 2022, 10:15 p.m.
Last Modified :
Sept. 20, 2022, 2:55 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-2022-35990.
| URL | Resource |
|---|---|
| https://github.com/tensorflow/tensorflow/commit/f3cf67ac5705f4f04721d15e485e192bb319feed | Patch Third Party Advisory |
| https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h7ff-cfc9-wmmh | 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-2022-35990 vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2022-35990 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.
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CVE Modified by [email protected]
May. 14, 2024
Action Type Old Value New Value -
Initial Analysis by [email protected]
Sep. 20, 2022
Action Type Old Value New Value 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/f3cf67ac5705f4f04721d15e485e192bb319feed No Types Assigned https://github.com/tensorflow/tensorflow/commit/f3cf67ac5705f4f04721d15e485e192bb319feed Patch, Third Party Advisory Changed Reference Type https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h7ff-cfc9-wmmh No Types Assigned https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h7ff-cfc9-wmmh Third Party Advisory Added CPE Configuration OR *cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* versions up to (excluding) 2.7.2 *cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* versions from (including) 2.8.0 up to (excluding) 2.8.1 *cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* versions from (including) 2.9.0 up to (excluding) 2.9.1 *cpe:2.3:a:google:tensorflow:2.10:rc0:*:*:*:*:*:* *cpe:2.3:a:google:tensorflow:2.10:rc1:*:*:*:*:*:* *cpe:2.3:a:google:tensorflow:2.10:rc2:*:*:*:*:*:* *cpe:2.3:a:google:tensorflow:2.10:rc3:*:*:*:*:*:*
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2022-35990 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-2022-35990
weaknesses.
Exploit Prediction
EPSS is a daily estimate of the probability of exploitation activity being observed over the next 30 days.
0.08 }} 0.00%
score
0.33963
percentile