CVE-2020-15265
"TensorFlow Out-of-Bounds Write"
Description
In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
INFO
Published Date :
Oct. 21, 2020, 9:15 p.m.
Last Modified :
Aug. 17, 2021, 1:21 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-2020-15265.
| URL | Resource |
|---|---|
| https://github.com/tensorflow/tensorflow/commit/eccb7ec454e6617738554a255d77f08e60ee0808 | Patch Third Party Advisory |
| https://github.com/tensorflow/tensorflow/issues/42105 | Patch Third Party Advisory |
| https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrfp-j2mp-hq9c | 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-2020-15265 vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2020-15265 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 -
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:*:*:*:*:-:*:*:* versions from (excluding) 2.4.0 OR *cpe:2.3:a:google:tensorflow:*:*:*:*:-:*:*:* versions from (excluding) 2.4.0 -
Initial Analysis by [email protected]
Nov. 03, 2020
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/eccb7ec454e6617738554a255d77f08e60ee0808 No Types Assigned https://github.com/tensorflow/tensorflow/commit/eccb7ec454e6617738554a255d77f08e60ee0808 Patch, Third Party Advisory Changed Reference Type https://github.com/tensorflow/tensorflow/issues/42105 No Types Assigned https://github.com/tensorflow/tensorflow/issues/42105 Patch, Third Party Advisory Changed Reference Type https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrfp-j2mp-hq9c No Types Assigned https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrfp-j2mp-hq9c Exploit, Patch, Third Party Advisory Added CPE Configuration OR *cpe:2.3:a:tensorflow:tensorflow:*:*:*:*:-:*:*:* versions up to (excluding) 2.4.0
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2020-15265 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-2020-15265
weaknesses.
Exploit Prediction
EPSS is a daily estimate of the probability of exploitation activity being observed over the next 30 days.
0.19 }} 0.03%
score
0.55591
percentile