CVE-2025-33124
6.5 · MEDIUMOverview
CVE-2025-33124 is a medium-severity vulnerability affecting ibm db2_merge_backup. It was published on February 17, 2026 and has a CVSS 3.1 base score of 6.5 (MEDIUM).
This vulnerability has a CVSS 3.1 base score of 6.5, rated MEDIUM. It can be exploited remotely over the network. Some level of privileges is required for exploitation.
Technical Description
IBM DB2 Merge Backup for Linux, UNIX and Windows 12.1.0.0 could allow an authenticated user to cause the program to crash due to the incorrect calculation of a buffer size.
Remediation
Check the references section for vendor advisories and patches from ibm. Update db2_merge_backup to the latest patched version. If immediate patching is not possible, review the CVSS vector to understand the attack surface and apply compensating controls such as network segmentation or access restrictions.
Affected Products
| Vendor | Product | Versions | Status |
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References
Frequently Asked Questions
What is CVE-2025-33124?
CVE-2025-33124 is a medium-severity vulnerability affecting ibm db2_merge_backup. It was published on February 17, 2026 and has a CVSS 3.1 base score of 6.5 (MEDIUM).
How severe is CVE-2025-33124?
This vulnerability has a CVSS 3.1 base score of 6.5, rated MEDIUM. It can be exploited remotely over the network. Some level of privileges is required for exploitation.
How do I fix or remediate CVE-2025-33124?
Check the references section for vendor advisories and patches from ibm. Update db2_merge_backup to the latest patched version. If immediate patching is not possible, review the CVSS vector to understand the attack surface and apply compensating controls such as network segmentation or access restrictions.
How can CyberStrike help with CVE-2025-33124?
CyberStrike's AI-powered security agents can automatically detect CVE-2025-33124 across your infrastructure using autonomous pentesting, DAST scanning, and HackBrowser. The platform continuously monitors for known vulnerabilities and provides actionable remediation guidance prioritized by real-world exploitability.
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