Ghita Mammar

– Risk consultant chez CAGIP (décembre 2024 - Present) – CISO Assistant chez la CNAM (mars 2023 - septembre 2024) at Ville de Paris – Threat vulnerability project manager chez L'Oréal (mai 2022 - mars 2023) at Levallois-Perret – Provided requirements on securing endpoints accessing to hybrid information system, aligning with a zero-trust security strategy for endpoints, covering an end-to-end security model (in the context of M2C Microsoft).

– According to NIST recommendation in migrating to a ZTA (Zero Trust Architecture) "The enterprise needs to make sure that the common elements (e.g., ID management, device management, event logging, etc.) are flexible enough to operate in a ZTA and legacy hybrid security architecture. Enterprise architects may also want to restrict ZTA candidate solutions to those that can interface with existing components." – In a context of M2C Microsoft my mission is to provide requirements on securing endpoints accessing to hybrid information system. – Those requirements align with a zero-trust security strategy for endpoints that covers an end-to-end security model.

– Assisted DBA team to enhance security of MYSQL databases, covering authentication, rights, privileges, traceability, backup/restoration, data confidentiality, fault tolerance, integrity, and data coherence. – Conducted risk analysis to strengthen MySQL database security. – Identified threats and studied attack scenarios to address primary security needs. – Proposed and implemented solutions for: – Authentication management – Privilege management – Password security – Traceability

– Mission: Etude technique de projet en R&D en technologies de l'information et la communcation

– Addressed web application security challenges, particularly SQL injection vulnerabilities. – Proposed a method to prevent SQL injection attacks for PHP applications, based on code review techniques suggested by OWASP. – Developed scripts to automatically parse code and localize vulnerable parameters in SQL queries within applications containing thousands of lines of code. – Conducted an in-depth study of SQL injection vulnerabilities to master and understand their causes. – Developed and automated a code review methodology through scripts to provide an effective solution against SQL injections.

– Research internship in Natural Language Processing and Data Mining applied to CyberSecurity. – Contributed to a research work titled: "Mining the Web for Collocations: IR Models of Term associations". – Focused on automatic collocation recognition and developed algorithms applicable to n-grams of arbitrary order, demonstrating effectiveness across various datasets.