À propos de Manh
Hello, I'm Manh, a cybersecurity expert with a passion for leading projects and securing digital landscapes. My expertise spans across pentesting, information security, DevSecOps, and applied machine learning, ensuring that your digital assets are secured and protected against the ever-evolving threat landscape.
Vietnamien
Bilingue ou natif
Anglais
Capacité professionnelle complète
Français
Capacité professionnelle complète
En télétravail uniquement
Travaille majoritairement à distance
Expériences
- SMESenior Research EngineerTÉLÉCOMMUNICATIONSfévrier 2021 - Aujourd'hui (5 ans et 4 mois)Paris, France
- Led the contributions in European projects from kick off to launch, including meetings, production of deliverables, presentation of results and patent drafting
- Designed, built and deployed a full-stack platform with explainability and resilience for user activities classification and anomaly detection in encrypted traffic
- Developed a SOAR solution leveraging the Shuffle SOAR platform to automatically orchestrate, refine, and execute playbooks in response to security incidents detected by SIEM systems
- Performed code review, pentest web/mobile apps and wrote scripts to perform different network attacks
- CEA-ListResearch EngineerENERGIEnovembre 2017 - janvier 2021 (3 ans et 3 mois)Palaiseau, France
- Integrated IDA Pro’s control-flow graphs into the BINSEC binary analysis platform
- Implemented UAFuzz, a binary-level fuzzer for Use-After-Free (UAF) detection, achieving 2x faster UAF detection (up to 43x) and discovered 11 new UAF bugs (7 CVEs). It was featured at BlackHat USA 2021, the French MISC cybersecurity magazine and in ACM Queue 2023 as highly inspiring for fuzzing research
- Developed AFLTeam, a tool utilizing graph structures and fuzzing data, employing partitioning and prioritized search algorithms to enhance code coverage (up to 16.4% improvement)
- National University of SingaporeResearch EngineerEDUCATION & E-LEARNINGseptembre 2014 - octobre 2017 (3 ans et 2 mois)Singapour, Singapour
- Developed and maintained AFLGo, a directed greybox fuzzer for patch testing (CI/CD) and bug reproduction, resulting in the discovery of 39 bugs (17 CVEs) and integration of AFLGo into Google’s OSS-Fuzz
- Implemented a novel, scalable automated program repair method using reference implementation analysis, significantly reducing overfitting and improving patch accuracy
- Conducted threat modelling, attack tree design, and penetration testing for Airbus’s unmanned Skyways security during design phase
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Formations
- PhD in Software SecurityGrenoble Alps University2021PhD thesis: Binary-level directed fuzzing for complex vulnerabilities
- Master 2 in Networking & TelecommunicationsUniversity of Paris Sud2013
Certifications
- Offensive Security Certified Professional (OSCP)Offensive Security2021
- Certified Red Team Professional (CRTP)Altered Security2021