NΞCTL

@intigriti Thank You... ♥️

@nevrectl Best of luck! Do keep us updated on your progress! 💪

Starting My New Journey at @intigriti, app.intigriti.com/profile/maruha… #bismillah

I just crushed the "Dojo #51 - DeadBolt" challenge on @YesWeHack! Ready to learn and pwn? 🌟 dojo-yeswehack.com/challenge/play… #YesWeHack #ChallengeAccepted

#QuiteTruth 🫠

One thing I’ve been experimenting with lately: Using #KiroSkills to operationalize #bugbounty #workflows instead of relying on scattered scripts, notes, and ad hoc prompts. I documented the approach here: builder.aws.com/content/3DuGU9… @AWSCommunity

Just published my latest project about the #rag-agent @Docker here: hub.docker.com/r/maruha/rag-a… I'll appreciate any feedback from you guys 🙏🏻

We've released two free lecture-levels from Fundamentals of ARM Exploitation today! One each from our 🔬Reverse Engineering🔬 and ⛓️ARM ROP⛓️ chapters. You can play through them right from your browser! Use this link, or the direct links below ⬇️ wargames.ret2.systems

Today's hoodie... another of my own designs

For anyone dealing with RASP protected apps, frida-strace is now your first step. Trace the syscalls, find what the app checks, hook those specific functions, bypass. No more guessing. Frida 17.8.0+, kernel 6.1+ required. #Frida #MobileSecurity #AppSec

@kmcnam1 It's why I use @deepseek_ai 🤣🤣🤣

Introducing the new /crawl endpoint - one API call and an entire site crawled. No scripts. No browser management. Just the content in HTML, Markdown, or JSON.

Built a #RAG implementation in #LocalLLM using #Ollama, #PGVector, and #Docling: • Multi-format ingestion (PDF, DOCX, PPTX, MP3 via Whisper) • Hybrid chunking + semantic search with source citations • Fully offline, Docker-ready Code + docs: n4igme.github.io/randscript/rag…

🚨 The #1 problem with local AI is now solved. There’s a new tool called llmfit that checks your hardware and tells you which models will run well before you download anything. So instead of guessing and hitting out-of-memory errors…it gives you a ranked list based on your machine. What it does (in one command): → scans your setup (RAM / CPU / GPU / VRAM) → evaluates models for quality, speed, fit, and context → selects the best quantization automatically → labels what’s ideal vs okay vs borderline The part I like most: it handles MoE models correctly. Example: Mixtral 8x7B has ~46.7B total params, but only ~12.9B are active per token, and llmfit accounts for that (a lot of tools still don’t). 100% Opensource.

Explained how Quantum computers work

Here is my @lmstudio config for @claudeai

Captures Android network traffic without proxies or certificates github.com/ProxymanApp/at…

bug hunting is over 😭🥀

Here's the vphone-aio for anyone cannot setup. I uploaded the whole VM into github so maybe cloning it might take a while. Follow the steps to run it. Also the VM already included rootless jailbreak environment and a few tweaks on it. github.com/34306/vphone-a…