VDB-208893 · CVE-2022-35973 · GHSA-689c-r7h2-fv9v

Google TensorFlow up to 2.7.1/2.8.0/2.9.0 QuantizedMatMul min_a/max_a/min_b/max_b denial of service

CVSS Meta Temp Score CVSS is a standardized scoring system to determine possibilities of attacks. The Temp Score considers temporal factors like disclosure, exploit and countermeasures. The unique Meta Score calculates the average score of different sources to provide a normalized scoring system.	Current Exploit Price (≈) Our analysts are monitoring exploit markets and are in contact with vulnerability brokers. The range indicates the observed or calculated exploit price to be seen on exploit markets. A good indicator to understand the monetary effort required for and the popularity of an attack.	CTI Interest Score Our Cyber Threat Intelligence team is monitoring different web sites, mailing lists, exploit markets and social media networks. The CTI Interest Score identifies the interest of attackers and the security community for this specific vulnerability in real-time. A high score indicates an elevated risk to be targeted for this vulnerability.
5.7	$0-$5k	0.00

A vulnerability, which was classified as problematic, was found in Google TensorFlow up to 2.7.1/2.8.0/2.9.0 (Artificial Intelligence Software). This affects the function QuantizedMatMul. The manipulation of the argument min_a/max_a/min_b/max_b with an unknown input leads to a denial of service vulnerability. CWE is classifying the issue as CWE-404. The product does not release or incorrectly releases a resource before it is made available for re-use. This is going to have an impact on availability. The summary by CVE is:

TensorFlow is an open source platform for machine learning. If `QuantizedMatMul` is given nonscalar input for: `min_a`, `max_a`, `min_b`, or `max_b` It gives a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. 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.

The weakness was presented 09/17/2022 as GHSA-689c-r7h2-fv9v. The advisory is shared at github.com. This vulnerability is uniquely identified as CVE-2022-35973 since 07/15/2022. Technical details are known, but no exploit is available. MITRE ATT&CK project uses the attack technique T1499 for this issue.

Upgrading to version 2.7.2, 2.8.1, 2.9.1 or 2.10.0 eliminates this vulnerability. Applying the patch aca766ac7693bf29ed0df55ad6bfcc78f35e7f48 is able to eliminate this problem. The bugfix is ready for download at github.com. The best possible mitigation is suggested to be upgrading to the latest version.

Productinfo

Type

Artificial Intelligence Software

Vendor

Google

Name

TensorFlow

Version

License

free

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 5.7
VulDB Meta Temp Score: 5.7

VulDB Base Score: 3.7
VulDB Temp Score: 3.6
VulDB Vector: 🔍
VulDB Reliability: 🔍

NVD Base Score: 7.5
NVD Vector: 🔍

CNA Base Score: 5.9
CNA Vector (GitHub, Inc.): 🔍

CVSSv2info

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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍

Exploitinginfo

Class: Denial of service
CWE: CWE-404
CAPEC: 🔍
ATT&CK: 🔍

Local: No
Remote: Yes

Availability: 🔍
Status: Not defined

EPSS Score: 🔍
EPSS Percentile: 🔍

Price Prediction: 🔍
Current Price Estimation: 🔍

0-Day	unlock	unlock	unlock	unlock
Today	unlock	unlock	unlock	unlock

Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: Upgrade
Status: 🔍

0-Day Time: 🔍

Upgrade: TensorFlow 2.7.2/2.8.1/2.9.1/2.10.0
Patch: aca766ac7693bf29ed0df55ad6bfcc78f35e7f48

Timelineinfo

07/15/2022 🔍
09/17/2022 +64 days 🔍
09/17/2022 +0 days 🔍
10/19/2022 +32 days 🔍

Sourcesinfo

Vendor: google.com

Advisory: GHSA-689c-r7h2-fv9v
Status: Confirmed

CVE: CVE-2022-35973 (🔍)

Entryinfo

Created: 09/17/2022 08:13 AM
Updated: 10/19/2022 02:47 PM
Changes: 09/17/2022 08:13 AM (55), 10/19/2022 02:47 PM (11)
Complete: 🔍
Cache ID: 18:7E3:40