CVE-2020-15201
Tensorflow Ragged TensorFlow Heap Buffer Overflow
Description
In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, the code is prone to heap buffer overflow. If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
INFO
Published Date :
Sept. 25, 2020, 7:15 p.m.
Last Modified :
Nov. 18, 2021, 5:24 p.m.
Source :
[email protected]
Remotely Exploitable :
Yes !
Impact Score :
2.5
Exploitability Score :
2.2
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-2020-15201
.
URL | Resource |
---|---|
https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02 | Patch Third Party Advisory |
https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1 | Third Party Advisory |
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4 | Exploit 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-2020-15201
vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2020-15201
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]
Nov. 18, 2021
Action Type Old Value New Value Added CWE NIST CWE-787 -
CPE Deprecation Remap by [email protected]
Aug. 17, 2021
Action Type Old Value New Value Changed CPE Configuration OR *cpe:2.3:a:tensorflow:tensorflow:2.3.0:*:*:*:-:*:*:* OR *cpe:2.3:a:google:tensorflow:2.3.0:*:*:*:-:*:*:* -
Initial Analysis by [email protected]
Oct. 01, 2020
Action Type Old Value New Value Added CVSS V2 NIST (AV:N/AC:M/Au:N/C:P/I:P/A:P) Added CVSS V3.1 NIST AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N Changed Reference Type https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02 No Types Assigned https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02 Patch, Third Party Advisory Changed Reference Type https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1 No Types Assigned https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1 Third Party Advisory Changed Reference Type https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4 No Types Assigned https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4 Exploit, Third Party Advisory Added CPE Configuration OR *cpe:2.3:a:tensorflow:tensorflow:2.3.0:*:*:*:-:*:*:*
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2020-15201
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-2020-15201
weaknesses.
Exploit Prediction
EPSS is a daily estimate of the probability of exploitation activity being observed over the next 30 days.
0.13 }} 0.02%
score
0.45949
percentile