CVE-2026-33734
Overview
CVE-2026-33734 is a known-severity vulnerability. It was published on July 6, 2026.
Technical Description
FOSSBilling is a free, open-source billing and client management system. Versions 0.6.0 through 0.7.2 have a SQL injection vulnerability in the `Massmailer` module filter functionality. An authenticated administrator can supply crafted filter values when updating a mass email message, causing untrusted input to be interpolated directly into SQL in the recipient selection query. Version 0.8.0 patches the issue. Some workarounds are available. Restrict administrator access to trusted users only, disable the `Massmailer` module if it is not required, audit existing records in the `mod_massmailer` table for suspicious filter values, and/or review administrator activity related to `Massmailer` message updates.
Remediation
Check the references section for vendor advisories, patches, and mitigation guidance. 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.
Frequently Asked Questions
What is CVE-2026-33734?
CVE-2026-33734 is a known-severity vulnerability. It was published on July 6, 2026.
How severe is CVE-2026-33734?
CVSS score information is not yet available for this vulnerability. Check back as the CVE record is updated by NVD analysts.
How do I fix or remediate CVE-2026-33734?
Check the references section for vendor advisories, patches, and mitigation guidance. 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-2026-33734?
CyberStrike's AI-powered security agents can automatically detect CVE-2026-33734 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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