A deep dive into the projects, initiatives, and technical work carried out during my apprenticeship as an SSI Engineer.
SFR Business is the B2B branch of the SFR Group, one of France's leading telecom operators. As an apprentice SSI Engineer within the IT Security team, my work spans IT Governance, risk management, internal AI tooling, automation, and operational security support across the group's enterprise infrastructure.
Contributed to the design and operational framing of an internal AI assistant dedicated to cybersecurity and governance activities. The objective was to accelerate security questionnaires, contractual and regulatory analysis, internal documentation search, and the preparation of structured responses on SSI, RGPD, NIS2, and DORA topics. The initiative was built around internal knowledge bases, controlled data exposure, and enterprise security constraints, with a strong focus on reliability, consistency, and practical support for day-to-day GRC work.
Worked on governance, risk, and compliance activities across several B2B scopes, combining operational security constraints with regulatory and contractual requirements. This included structured risk analysis work, support on supplier security assessments, contribution to NIS2 and DORA readiness topics, participation in internal compliance efforts, and production of material used for reporting and remediation follow-up. The role required bridging technical realities, business expectations, and formal security governance.
Contributed to security governance through project reviews, policy support, awareness material, and the integration of security requirements into operational processes. Activities covered project security framing, alignment with internal policies, support on contractual and supplier-related security topics, and participation in broader security-by-design efforts. This work sat at the intersection of governance, documentation, process formalization, and stakeholder coordination.
Built and improved several Excel-based automation workflows used for security reporting, KPI tracking, consolidation of scattered data sources, and recurring governance deliverables. This included macros, formulas, structured dashboards, and automation logic designed to reduce manual work, improve data consistency, and make reporting more reliable over time. These tools supported operational follow-up on audits, compliance, project monitoring, and broader SSI governance activities.
Developed an internal cybersecurity utility in Go to perform technical checks without depending on external online services. The tool was designed to keep analysis in-house while providing fast and practical security insights such as HTTP response analysis, TLS and certificate inspection, DNS checks, and evaluation of exposed security headers. Built with performance and simplicity in mind, it combines concurrent processing with a lightweight architecture to support internal security assessment workflows.
Full-stack image processing pipeline built entirely in C. Implements a custom neural network from scratch — no external ML libraries. Handles grayscale conversion, grid detection and straightening, character segmentation, and final puzzle resolution. GTK 3.0 and SDL for the graphical interface. One of the most technically demanding projects of the cycle, representing 96%+ C codebase.
View repositoryCooperative maze game developed in a team during the first year of integrated prépa. Full Python implementation with Poetry for dependency management, Conventional Commits, Google-style docstrings, Pdoc3 documentation, and an integrated logging system. A project as much about software engineering methodology as about game design.
View repositoryAn educational Linux kernel rootkit developed in C to understand deep system mechanics, kernel module programming, and evasion techniques. Focuses on hooking syscalls and manipulating kernel data structures. Developed strictly for educational and defensive understanding.
View repositoryiOS personal finance app built entirely in Swift — SwiftUI, SwiftData with versioned schema and migration, and on-device ML via CoreML/NaturalLanguage for automatic transaction categorization with local adaptive learning. Security-first: Face ID/Touch ID, AES-GCM encryption for sensitive data, SHA-256 integrity checks, and Keychain key management with rotation. Multi-currency support, savings goals, PDF export, and encrypted local backups. Zero external service dependency.
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