Vulnerability Researcher in KR 👋 / / [email protected]
Seoul, Republic of Korea
Joined July 2025
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- Following126
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DongHa Lee retweeted
Galaxy S26 Ultra: untrusted_app → root.
Introducing "Infinity Core": 6 vulns in the Linux kernel's core subsystems.
Their impact spans Linux server LPE, container escape, and Android LPE.
Details: github.com/V4bel/InfinityCor…
DongHa Lee retweeted
Learn macOS vulnerability research from Gergely (@gergely_kalman) & Csaba (@theevilbit) at #OBTS v9!
More on their training + all our other #OBTS trainings:
objectivebythesea.org/v9/tra…
DongHa Lee retweeted
I finally tested GPT-6 Sol on a real work. 2 repos. 105 hidden bugs. Find and fixed what you can.
It looks like a huge degradation. The results:
- GPT-6 Astra (max): 45
- GPT-5.6 Sol (max): 43.5
- Opus 5.5 (max): 41.7
- Muse Spark 1.3 (max): 32.2
- GPT-6 Sol (max): 29.3
Until you measure the cost (API-equivalent):
- GPT-6 Astra (max): $33.04
- GPT-5.6 Sol (max): $95.25
- Opus 5.5 (max): $58.53
- Muse Spark 1.3 (max): $18.11
- GPT-6 Sol (max): $9.93
More effort levels (xhigh, high, medium, low) dropping in this thread today 🧵
DongHa Lee retweeted
I got the latest iOS and macOS 27 booting in Qemu (with SPTM!)
- Virtual iPhone 17, 16, 15, 14, 13, 12 and every M1-M5 Mac supported
- Debug, patch, or modify everything: kernel, SPTM, TXM, launchd, dyld, user programs all modifiable/ GDB-able
- Boots directly to root shell in seconds
- Run your own programs as root in iOS/ macOS, no jailbreak / kernel patches required
- SPTM, TXM, MTE/MIE, genter/ gexit, GXF/SPRR/GL0-2, AMCC, AIC v1-3, Apple timer, many sysregs
- Automated setup; get running in just a few minutes
- Runs anywhere qemu runs... no ARM CPU required 😉
Try it here: github.com/jprx/darwin-vm
DongHa Lee retweeted
Runs macOS on iPad to enable pro apps like Xcode and Terminal directly on the device
github.com/nfzerox/VirtualMa…
DongHa Lee retweeted
Modern iOS Security Features – A Deep Dive into SPTM, TXM, and Exclaves
Paper: arxiv.org/pdf/2510.09272
Author: Moritz Steffin and Jiska Classen
DongHa Lee retweeted
We’re excited to announce that the NDSS Symposium 2027 will take place in Seoul, Republic of Korea.
This marks an exciting next chapter for the symposium that reflects the global reach of cybersecurity research.
Read more: internetsociety.org/blog/202…
DongHa Lee retweeted
Had some fun with new usbliter8 bootrom exploit. Got root shell yesterday by booting custom iOS 27.0b2 firmware on iPhone 11 Pro.
Honestly, it's not practical for daily use. For some reason, baseband, Wi-Fi, and USB connections are completely broken.
DongHa Lee retweeted
NVIDIA da acceso gratis por API a modelos de IA.
A DeepSeek V4, MiniMax M2.7, GLM 5.1, Gemma 4...
Perfecto para pruebas de desarrollo.
Puedes usarlo con OpenCode y OpenClaw
Puedes conseguir acceso aquí:
→ build.nvidia.com/models
ALT Captura de la web de NVIDIA Build en la sección “Models”, mostrando un listado de modelos de IA optimizados por NVIDIA con el filtro “Free Endpoint” activado. Se ven 156 modelos disponibles, tarjetas como deepseek-v4-flash, deepseek-v4-pro, glm-5.1 y glm-4.7, además de buscador, filtros por casos de uso y ordenación por “Most Recent”. NVIDIA sacando buffet libre de modelos como quien no quiere la cosa.
DongHa Lee retweeted
[1/2]
CVE-2026-32223: heap overflow in usbprint.sys (IOCTL 0x220064).
Malformed USB descriptor, Named Pipe spray + Ghost Chunk for kernel leak, forged IRP, SYSTEM.
Writeup: enki.co.kr/en/media-center/b…
#CVE_2026_32223 #WindowsKernel #LPE #vulnresearch
IPv6 isn’t the end
but this IPv8 draft feels like it was LLM-generated and tries to cram everything in, and bringing in JWT makes no sense
ietf.org/archive/id/draft-th…
DongHa Lee retweeted
What if I told you the first GPU neural network implementation happened in Korea in 2004? 😗
Before CUDA, Before modern deep learning hype.
The world’s FIRST GPU-accelerated neural network wasn’t built in Silicon Valley or by NVIDIA,
It came from South Korea’s Soongsil University in 2004, years before CUDA even existed.
two Korean researchers, Kyoung-Su Oh and Keechul Jung at Soongsil University quietly implemented neural networks on a consumer ATI Radeon GPU and achieved massive speedups.
Used an ATI Radeon 9700 Pro to get 20-30x speedups on matrix multiplications and sigmoid functions for real-time text detection.
translate then read
- koreascience.or.kr/article/J…
