Resource exhaustion in TensorFlow - CVE-2022-41898
Published: February 21, 2024
Vulnerability identifier: #VU86675
CSH Severity: Medium
CVSS v4: 8.7 [CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N]
CVE-ID: CVE-2022-41898
CWE-ID: CWE-400
Exploitation vector: Remote access
Exploit availability:
No public exploit available
Vulnerability details
The vulnerability allows a remote attacker to perform a denial of service (DoS) attack.
The vulnerability exists due to TensorFlow will crash if `SparseFillEmptyRowsGrad` is given empty inputs. A remote attacker can trigger resource exhaustion and perform a denial of service (DoS) attack.
Affected software
TensorFlow
IBM Watson Assistant for IBM Cloud Pak for Data
IBM Watson Discovery for IBM Cloud Pak for Data
IBM Maximo Application Suite
Robotic Process Automation for Cloud Pak
IBM Watson Assistant for IBM Cloud Pak for Data
IBM Watson Discovery for IBM Cloud Pak for Data
IBM Maximo Application Suite
Robotic Process Automation for Cloud Pak
How to mitigate CVE-2022-41898
Install updates from vendor's website.
TensorFlow - addressed in versions 2.8.4, 2.9.3, 2.10.1, 2.11.0
IBM Watson Assistant for IBM Cloud Pak for Data - update to 4.7.0
IBM Watson Discovery for IBM Cloud Pak for Data - update to 4.6.2
IBM Maximo Application Suite - addressed in versions 8.9.6, 8.10.3
Robotic Process Automation for Cloud Pak - addressed in versions 21.0.7.1, 23.0.1
IBM Watson Assistant for IBM Cloud Pak for Data - update to 4.7.0
IBM Watson Discovery for IBM Cloud Pak for Data - update to 4.6.2
IBM Maximo Application Suite - addressed in versions 8.9.6, 8.10.3
Robotic Process Automation for Cloud Pak - addressed in versions 21.0.7.1, 23.0.1
External References
Related Security Bulletins
- Multiple vulnerabilities in IBM Robotic Process Automation for Cloud Pak
- Multiple vulnerabilities in IBM Maximo Application Suite
- Multiple vulnerabilities in IBM Watson Discovery Cartridge for IBM Cloud Pak for Data
- Multiple vulnerabilities in IBM Watson Assistant for IBM Cloud Pak for Data
- Multiple vulnerabilities in TensorFlow