Mindsdb

MindsDB is an open-source machine-learning infrastructure platform designed to integrate AI models with databases and applications, maintaining a concentrated but prominent footprint in the ML-ops and data-integration landscape. Vulnerabilities affecting the vendor skew toward serious outcomes, with an elevated share reaching critical severity and a moderate tendency toward public exploit availability, reflecting the inherent risks of dynamic code generation and data-processing intermediaries. The exposure concentrates in the core MindsDB platform and recurs through weakness classes centered on code injection, eval injection, path traversal, unsafe deserialization, and server-side request forgery—attack vectors endemic to systems that execute user-supplied logic or bridge untrusted data sources to privileged backend systems. Defenders should treat MindsDB deployments as high-value targets for code-execution attacks, particularly in environments where the platform bridges to sensitive databases or production infrastructure, and should prioritize patching releases that address injection and deserialization flaws. Live severity, exploitation, and exposure counts are shown alongside this summary.