CVE-2026-75062
Overview
CVE-2026-75062 is a known-severity vulnerability. It was published on August 26, 2026.
Technical Description
Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection') in the default lf.query Python protocol in Google langfun versions prior to 0.1.2 allows remote unauthenticated attackers to execute arbitrary Python code in the context of the host application via crafted prompt inputs that cause the model to generate executable Python expressions evaluated without a sandbox.
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-2026-75062?
CVE-2026-75062 is a known-severity vulnerability. It was published on August 26, 2026.
How severe is CVE-2026-75062?
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-2026-75062?
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-2026-75062?
CyberStrike's AI-powered security agents can automatically detect CVE-2026-75062 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.
How CyberStrike Helps
AI agents map your attack surface to find vulnerabilities like this one.
Automated penetration testing that runs continuously, not just quarterly.
AI-driven PR review catches vulnerable dependencies before they ship.
Browser-based exploitation validates findings with real proof-of-concept.