Martin Mareš is a Senior Security Consultant based in Prague with 29 years of experience securing cloud-native and performance-sensitive systems. He blends hands-on engineering—hardening custom WSL distributions, containerized environments, and Kubernetes—with practical governance work aligning large customers to standards like DORA and ISO/IEC 27001. As an application architect and consultant he has migrated systems to Azure, improved runtime security with service mesh tooling, and led monitoring and incident-resolution efforts for financial workloads. He contributes to low-level open-source tooling (notably improving process sandboxing and robustness in the isolate sandbox and enhancing pciutils output), showing attention to reliability, resource limits and race-condition fixes. Martin also teaches DevOps and algorithms, and has led industry–academia projects that bring applied AI and open data into student-led production work. Quietly pragmatic, he pairs deep systems-level skills with a knack for making complex security controls usable for engineering teams.
29 years of coding experience
23 years of employment as a software developer
Ph.D., Computer science, Ph.D., Computer science at Charles University
Contributions:3 releases, 35 reviews, 145 commits in 5 years 11 months
Contributions summary:Martin primarily contributed to improving the display of memory ranges behind a bridge in the `lspci` utility. Their work involved modifying the `lspci.c` file to provide better output based on verbosity levels and handling for empty or non-empty ranges. The user also cleaned up code in `ls-caps.c` and modified `lib/types.h` and `ls-vpd.c` to accommodate the changes.
Contributions:106 commits, 32 PRs, 207 pushes in 6 years 7 months
Contributions summary:Martin primarily contributed to the core functionality of the `isolate` project, focusing on enhancements to process sandboxing and resource management. They improved the system's robustness through signal handling cleanup, addressing race conditions and internal errors. The user also implemented features such as silent mode and configurable resource limits, demonstrating a focus on usability and control over the sandboxed environment. Furthermore, they refactored the code to improve maintainability by splitting the source into multiple files.
seccompsecuritysandboxprogramsuntrusted
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.