
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.

reverse engineering SynthID for text

A new simple and powerfull packer for malware

Python proof-of-concept demonstrating IPFS CID spoofing via multihash length extension, highlighting content-addressing verification flaws that can…

Python PoC demonstrating CVE-2026-22020: exploitable weak seed in quantum key distribution privacy amplification, reducing final key entropy.

Advanced EDR Evasion via AI Telemetry Spoofing & WASM Sandboxing. Project Onyx is a PoC Red Team pipeline designed to demonstrate advanced evasion…

Official repository for CTFTiny