CVE-2022-23591
TensorFlow Self Recursion Stack Overflow Vulnerability
Description
Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
INFO
Published Date :
Feb. 4, 2022, 11:15 p.m.
Last Modified :
June 27, 2023, 2:40 a.m.
Source :
[email protected]
Remotely Exploitable :
Yes !
Impact Score :
3.6
Exploitability Score :
3.9
Public PoC/Exploit Available at Github
CVE-2022-23591 has a 2 public PoC/Exploit available at Github.
Go to the Public Exploits tab to see the list.
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-2022-23591.
| URL | Resource |
|---|---|
| https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c | Patch Third Party Advisory |
| https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7 | 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).
None
HTML
test 反向辣鸡数据投放 CVE-2022-23305 工具 利用 教程 Exploit POC
cve-2020-
Results are limited to the first 15 repositories due to potential performance issues.
The following list is the news that have been mention
CVE-2022-23591 vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2022-23591 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 -
Reanalysis by [email protected]
Jun. 27, 2023
Action Type Old Value New Value Added CWE NIST CWE-674 -
Initial Analysis by [email protected]
Feb. 10, 2022
Action Type Old Value New Value Added CVSS V2 NIST (AV:N/AC:L/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/448a16182065bd08a202d9057dd8ca541e67996c No Types Assigned https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c Patch, Third Party Advisory Changed Reference Type https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7 No Types Assigned https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7 Patch, Third Party Advisory Added CPE Configuration OR *cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* versions up to (including) 2.5.2 *cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* versions from (including) 2.6.0 up to (including) 2.6.2 *cpe:2.3:a:google:tensorflow:2.7.0:*:*:*:*:*:*:*
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2022-23591 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-2022-23591
weaknesses.
Exploit Prediction
EPSS is a daily estimate of the probability of exploitation activity being observed over the next 30 days.
0.09 }} -0.01%
score
0.36685
percentile