About Me

I am Jaeyeong Lee, a security researcher focused on operating-system security, vulnerability research, reverse engineering, fuzzing, program analysis, and automated vulnerability discovery. My research experience spans macOS, virtualization, embedded and IoT systems, and large open-source software projects.

Education
Sunrin Internet High School, Information Security (2023.3 ~ 2026.2)Seoul Women's University, Cybersecurity Gifted Education Institute — High-Level Specialized Class A, White Hat Track (2024.05 ~ 2024.11)

Experience

  • STEALIEN Inc.
    Penetration Testing Team Intern
    2026.03 ~ 2026.06
  • HSPACE
    Field Trainee
    2025.07 ~ 2025.08

News

Sep 2026Presenting at EMUCON (Canberra).
Mar 2026Participating in SECCON CTF Finals 2026 (Tokyo).
Feb 2026Accepted to KCSE 2026 (Ulsan).

Publications

  • Race to Charge: Concurrency Bugs and State Integrity Violations in EV Charging Infrastructure
    Jaeyeong Lee and Seonhyeong Lee
    VehicleSec '26, USENIX Conference, 2026
  • ExplosionGuard: Policy Synthesis and Guardrails for Budget-Constrained Symbolic Execution
    Jaeyeong Lee and GeonWoo Lee
    Korea Conference on Software Engineering (KCSE), 2026
View All Publications →

Vulnerability Research

  • CVE-2026-43783 (Apple DesktopServices)
    Race condition leading to root privilege escalation
  • CVE-2026-43805 (Apple IOKit)
    Race condition allowing kernel memory writes
  • CVE-2026-28969 (Apple IOKit)
    Use-after-free causing unexpected system termination
View All Research →

Talks & Presentations

  • Zero-Click to Root: Breaking IoT Security Without Authentication
    EMUCON
  • Pre-Auth RCE in IPCAM : How I Became Big Brother
    HolyShield Conference
View All Talks →

Honors & Awards

  • 20266th Place, SECCON CTF International Finals 2026
  • 20251st Place, HITCON CTF 2025
  • 2025Certificate of Commendation, KORAIL
View All Honors →

Projects

Blind penetration test for Hyundai Mobis overseas subsidiaries

2025.09.22 ~ 2025.11.14

Automated Analysis of IoT Vulnerabilities with Taint Analysis

Research project focusing on detecting vulnerabilities in IoT devices using taint analysis techniques.

Intelligent Traffic Analysis Training Data Generation — Cyber Operations Command

Generated standard and malicious traffic datasets for training intelligent analysis models.
View All Projects →