Stephan Brandauer is a founding software engineer in Munich with 14 years of experience building AI-driven security tooling and SAST/ML systems. He led static analysis and machine-learning efforts at GitHub, contributing to the widely used CodeQL project—adding TypeScript support, adaptive threat-modeling refactors, and new import/parameter analysis features—and now applies that expertise to an AI-based security triage product at Maze. His career spans cloud-native backend development (Node.js/TypeScript, Kubernetes, Terraform) and organizational DevOps leadership in e-mobility, where he drove CI/CD adoption and measurable delivery improvements. He holds a PhD in computer science on alias control and ran dynamic analyses that measured aliasing in the wild, combining compiler research with practical security engineering.
14 years of coding experience
5 years of employment as a software developer
Bachelor of Science (B.Sc.), Cognitive Informatics, Bachelor of Science (B.Sc.), Cognitive Informatics at Universität Bielefeld
CodeQL: the libraries and queries that power security researchers around the world, as well as code scanning in GitHub Advanced Security
Role in this project:
Back-end Developer
Contributions:379 reviews, 250 commits, 91 PRs in 1 year
Contributions summary:Stephan's commits primarily focus on enhancing the CodeQL codebase for supporting TypeScript. They updated tests for TypeScript 4.7, which involved modifying existing test files and adding support for new file extensions (.mts and .cts). Further contributions included refactoring code, specifically the endpoint features within the adaptive threat modeling library, and adding new features related to listing imports and parameter names, indicating a focus on improving code analysis and security features.
Contributions:191 pushes, 1 branch in 1 year 2 months
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Stephan Brandauer - Founding Software Engineer at Maze