
ML-for-RNGs
Demonstrates using machine learning to predict random number generator sequences, highlighting cryptographic weaknesses through adversarial analysis.

Demonstrates using machine learning to predict random number generator sequences, highlighting cryptographic weaknesses through adversarial analysis.

A Bumblebee-inspired Crypter

a small wiper malware programmed in c#

Windows And Ways To Break It

D/Invoke implementation in Nim

ShellcodeFluctuation PoC ported to Nim

Tools that trigger False Positive AV alerts

Windows 10 DLL Injector via Driver utilizing VAD and hiding the loaded driver

Hardware Breakpoint (DR0-DR7) based patch-less user-mode hooking & telemetry instrumentation engine (AMSI, WLDP & ETW PoC).

Detection rule validation

PoC MSI payload based on ASEC/AhnLab's blog post


CEREBRO-RED v2: Advanced LLM Red Team Research Platform with PAIR Algorithm and LLM-as-a-Judge Evaluation

CVPR2023: Unlearnable Clusters: Towards Label-agnostic Unlearnable Examples

Reverse Shell Detection with Machine Learning

CVE-2026-6765, Test only FormAutofill handlers exposed in Firefox

Browser PoC demonstrating CVE-2026-2828, a WebGPU timing side-channel that leaks cross-origin iframe pixel values by measuring GPU timestamp-query…

Spawns macOS programs through launchd's private XPC interface without execing them, making EDR record launchd as parent. Supports one-shot,…