
Raphael Campos contributed to aquasecurity/tracee by engineering kernel-level data filtering, extensibility frameworks, and robust deployment workflows over eight months. He enhanced event processing with eBPF and C, optimizing memory usage and enabling scalable, policy-driven monitoring. Raphael expanded CI/CD coverage and integration testing in Go, ensuring compatibility across kernel versions and improving release reliability. He developed ELF file analysis tools for cross-architecture validation, strengthened dependency management, and improved build reproducibility with Go Modules. His work established a modular backend architecture, improved observability and debugging, and delivered reliable, maintainable solutions for security monitoring and instrumentation in complex system environments.
February 2026: Focused on strengthening cross-environment ELF analysis capabilities in aquasecurity/tracee. Delivered ELF File Analysis Tools with Host Architecture Compatibility, enabling reliable parsing and validation of ELF binaries across different host architectures and machine types. This work improves accuracy of instrumentation and reduces environment-specific issues, delivering tangible risk reduction for security assessments and incident response. No major bugs fixed this month; stability improvements were pursued through helper utilities and code hygiene. Technologies demonstrated: Go, ELF parsing, architecture-aware validation, and maintainability practices.
February 2026: Focused on strengthening cross-environment ELF analysis capabilities in aquasecurity/tracee. Delivered ELF File Analysis Tools with Host Architecture Compatibility, enabling reliable parsing and validation of ELF binaries across different host architectures and machine types. This work improves accuracy of instrumentation and reduces environment-specific issues, delivering tangible risk reduction for security assessments and incident response. No major bugs fixed this month; stability improvements were pursued through helper utilities and code hygiene. Technologies demonstrated: Go, ELF parsing, architecture-aware validation, and maintainability practices.
October 2025 (2025-10) performance overview for aquasecurity/tracee. Delivered a foundational extension framework with global registry and lifecycle-aware interfaces, enabling dynamic extensions such as signal handling, probe group registration, and event derivations; improved observability by ensuring all probe types are logged during probe loading; and memory management improvements increasing the maximum non-network byte array size to 32KB to better handle larger payloads while maintaining safeguards. These changes establish a scalable, modular architecture, improve debugging and troubleshooting efficiency, and enhance payload resilience under higher load.
October 2025 (2025-10) performance overview for aquasecurity/tracee. Delivered a foundational extension framework with global registry and lifecycle-aware interfaces, enabling dynamic extensions such as signal handling, probe group registration, and event derivations; improved observability by ensuring all probe types are logged during probe loading; and memory management improvements increasing the maximum non-network byte array size to 32KB to better handle larger payloads while maintaining safeguards. These changes establish a scalable, modular architecture, improve debugging and troubleshooting efficiency, and enhance payload resilience under higher load.
April 2025 monthly summary for aquasecurity/tracee. Key goals were to improve build reliability, cross-environment consistency, and runtime verification stability.
April 2025 monthly summary for aquasecurity/tracee. Key goals were to improve build reliability, cross-environment consistency, and runtime verification stability.
February 2025: Consolidated feature work and robustness improvements in aquasecurity/tracee, delivering improved event parsing, verified policy-based filtering, and dependable dependency management. The work enhances monitoring accuracy, reduces false positives, and improves maintainability through clearer naming and tests.
February 2025: Consolidated feature work and robustness improvements in aquasecurity/tracee, delivering improved event parsing, verified policy-based filtering, and dependable dependency management. The work enhances monitoring accuracy, reduces false positives, and improves maintainability through clearer naming and tests.
January 2025 monthly summary for aquasecurity/tracee focused on reliability improvements, test coverage expansion, and dependency maintenance to strengthen policy enforcement, reporting accuracy, and maintainability. Major delivered features include robustness in kernel data filtering and tracing reliability, expanded integration test coverage for event filters, and an updated dependency stack with libbpfgo. These efforts improve multi-policy enablement across all filter configurations, enhance termination reporting accuracy, reduce regression risk through broader tests, and enable access to bug fixes and new features from dependencies.
January 2025 monthly summary for aquasecurity/tracee focused on reliability improvements, test coverage expansion, and dependency maintenance to strengthen policy enforcement, reporting accuracy, and maintainability. Major delivered features include robustness in kernel data filtering and tracing reliability, expanded integration test coverage for event filters, and an updated dependency stack with libbpfgo. These efforts improve multi-policy enablement across all filter configurations, enhance termination reporting accuracy, reduce regression risk through broader tests, and enable access to bug fixes and new features from dependencies.
December 2024 — Delivered kernel data filtering enhancements, expanded CI/CD coverage for kernel compatibility, and fixed critical EBPF/ABI alignment. These efforts strengthened security monitoring across newer kernels, improved testing reliability, and accelerated safe deployment cycles. Technologies demonstrated include eBPF, kernel data filtering semantics, CI/CD automation, CodeQL, and robust test/documentation workflows.
December 2024 — Delivered kernel data filtering enhancements, expanded CI/CD coverage for kernel compatibility, and fixed critical EBPF/ABI alignment. These efforts strengthened security monitoring across newer kernels, improved testing reliability, and accelerated safe deployment cycles. Technologies demonstrated include eBPF, kernel data filtering semantics, CI/CD automation, CodeQL, and robust test/documentation workflows.
October 2024: Focused on release readiness for Tracee. Delivered 0.22.3 deployment and Helm chart updates, tightening deployment artifacts and ensuring references point to the latest image. No critical bugs fixed this month; efforts centered on alignment with the new release, artifacts consistency, and release traceability.
October 2024: Focused on release readiness for Tracee. Delivered 0.22.3 deployment and Helm chart updates, tightening deployment artifacts and ensuring references point to the latest image. No critical bugs fixed this month; efforts centered on alignment with the new release, artifacts consistency, and release traceability.
Summary for 2024-09: Focused on strengthening Tracee's kernel-level data filtering and memory efficiency in the eBPF subsystem. Key features delivered include kernel eBPF data filtering enhancements for event processing and an LPM Trie memory optimization using the BPF_F_NO_PREALLOC flag. This work increases filtering precision, reduces memory footprint, and enables scalable monitoring for larger deployments. There were no high-severity bugs fixed this month. Overall impact: improved throughput and accuracy of event filtering, lower memory usage, and a stronger foundation for future expansions in kernel data processing. Technologies/skills demonstrated: eBPF programming, kernel data filtering, LPM Trie structures, memory optimization techniques, use of map-based management for dynamic filter criteria, and commit-driven development practices.
Summary for 2024-09: Focused on strengthening Tracee's kernel-level data filtering and memory efficiency in the eBPF subsystem. Key features delivered include kernel eBPF data filtering enhancements for event processing and an LPM Trie memory optimization using the BPF_F_NO_PREALLOC flag. This work increases filtering precision, reduces memory footprint, and enables scalable monitoring for larger deployments. There were no high-severity bugs fixed this month. Overall impact: improved throughput and accuracy of event filtering, lower memory usage, and a stronger foundation for future expansions in kernel data processing. Technologies/skills demonstrated: eBPF programming, kernel data filtering, LPM Trie structures, memory optimization techniques, use of map-based management for dynamic filter criteria, and commit-driven development practices.

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