Hello everyone,

I'm a Pwn CTF player with a strong passion for binary exploitation, low-level programming, and understanding how things work under the hood...... But these days I think I face problems in thi carrer starting from what to learn to how to do it to is it even right to learn with AI, so I need aome advices in this field and what should I focuses on as someone whose goal is to a skilled exploit developer and ofc for real world so should continue with ctf like pwn.college(I am very close to finish yellow belt) and should i master reverse engineering with details and low level programming and memory management to reach my goals and the most important thing is it worth it as a carrer especially when AI can do everything....

Hey everyone, I am the creator of OshoosiClaw (OpenỌ̀ṣọ́ọ̀sì), an open source autonomous Endpoint Detection and Response agent built in Rust for Linux and Windows.

Traditional user mode sensors often rely on cloud telemetry and remain vulnerable to kernel callback blinding, BYOVD handle stripping, and modern AI agent breakouts. I built OshoosiClaw to operate as a local first, decentralized immune system that enforces security directly at the kernel and hardware boundaries while keeping its working set under 250 MB.

On the defense side, it pairs a Windows Ring 0 Minifilter and ELAM driver with Linux BPF_PROG_TYPE_LSM hooks and a sub 20 microsecond Cgroup v2 freezer quarantine. It includes an in memory 101 table SQL telemetry engine (siquery), an autonomous reverse engineering subsystem using Magika and YARA X synthesis, a 14 engine detection pipeline, and multi ring containment mapped to MITRE ATT&CK and ATLAS for local AI agents. Nodes share intelligence over a libp2p GossipSub mesh secured with hybrid post quantum cryptography (ML KEM 768 and ML DSA 65), BLAKE3 Merkle audit chains, and differential privacy.

I am looking for both Rust developers and offensive security folks or pentesters to put this through its paces:

For Pentesters and Red Teamers: I want you to try and break it. Throw your custom loaders, process hollowing techniques, unhooking PoCs, BYOVD payloads, and prompt injection or agent breakout chains at it. You can also run the built in 16 vector adversarial gauntlet (osoosi redteam --suite all) or test against the active thread tarpit and synthetic anti blinding canaries to see where the detection or containment logic folds.

For Rust and Kernel Developers: If you enjoy working on eBPF, Windows kernel drivers, low latency systems programming, P2P networking, or local ML inference, I would love your eyes on the architecture, code quality, and performance bottlenecks.

Pre built v1.2.0 packages (.msi, .deb, .rpm, and hardened Docker images) and full source are live on GitHub:https://github.com/oyesanyf/OshoosiClaw

If you find a bypass, trigger a false positive, or want to contribute a crate improvement, please open an issue or PR, or drop a comment below. Looking forward to your feedback.

oyesanyf

Hey everyone,

Transitioning from Windows exploit dev to iOS vulnerability research. I'm currently deciding between two Mac mini options at the same price point:

Option A: M5 Pro (24GB RAM / 512GB SSD)

Option B: M6 Base (32GB RAM / 1TB SSD)

My setup & workflow:

3-monitor workstation setup (though I'm willing to trade/drop one monitor if going for 32GB RAM is objectively better).

Heavy static analysis in IDA Pro / Binary Ninja (dyld shared cache & XNU).

Tethered debugging (lldb/Frida) on a physical iPhone X.

The Dilemma:

The base M6 is hardware-limited to 2 external displays, while the M5 Pro handles 3 native displays.

Since I believe target execution happens on physical hardware, is 24GB RAM on the M5 Pro enough? Or would you trade a monitor to get 32GB RAM on the base M6?

Thanks!

So I’ve been really interested in learning reverse engineering for a while and only tried my hand at a few crackmes so far. I found reverse engineering interesting because it feels rewarding to be able to piece together what the original code might have looked like and why the program behaves the way it does. I liked identifying variables and reconstructing data structures by reading the assembly or generated pseudo code by tools like ghidra since getting them right felt rewarding. Recently with AI becoming really good at the same things, I’m left wondering whether it’s worth it to learn these skills anymore. People were able to decompile and port entire games just using AI much faster than any person can. It’s left me feeling really discouraged about reverse engineering and wondering whether I should focus on other areas of exploit dev

hey there so i will be straight to the point iam learning c right now and my current roadmap is this first learn c from the beej guide to c programming and then learn assembly from this resources https://0xinfection.xyz/reversing/pages/part-1-the-cyber-revolution.html and then learn windows internal and then finally heavnly wizardy 101 so my question is that is dsa necessary to become malware analyst do i need to grind the leetcode as well what do you guys says and currently i have finished pointers struc and typedef from the beej guide and iam currently right now in memory allocation so guys please tell me should i follow this roadmap and not learn dsa and also how is my roadmap including my resources.

I'm a beginner-to-intermediate CTF player focusing on reverse engineering and binary exploitation.

My usual workflow is to attempt a challenge myself, then sometimes let AI solve the binary when I'm completely stuck. I don't immediately copy the solution into a writeup. I reproduce the steps in my own environment, ask follow-up questions to understand the reasoning, cross-reference the explanations with documentation and Google, and write my own explanation in Word.

I believe reading writeups is a legitimate way to learn, and we don't need to reinvent the wheel every time. However, I'm concerned that letting AI solve the challenge first might prevent me from developing independent problem-solving skills.

For experienced RE/pwn players:

Is this a reasonable way to learn?

Where do you draw the line between AI-assisted and AI-solved?

Should I spend more time struggling with challenges before asking AI?

How do you ensure you can solve unfamiliar binaries independently?

Should I not use the AI completely?

I'd appreciate your honest opinions and advice!

Am I the only one who finds it annoying when a website uses .blob URLs for media/content that can only be played inside that specific page?

I was wondering if it would be possible to build a browser extension that hooks into SourceBuffer.appendBuffer() and observes the binary chunks being passed to it.

The concept would be pretty simple:

Server → encrypted/chunked data → browser → appendBuffer() → decoder/player

The extension would collect the buffers as they arrive, keep them in the correct order, and potentially reconstruct the original resource from those fragments.

Not talking about breaking DRM or decrypting something the browser itself can't decrypt. More like:

If the browser receives and processes the data, why can't we have a DevTools-like tool that lets us inspect and reconstruct those buffers?

Something like a "Blob Inspector":

• Intercept appendBuffer() calls
• See the individual chunks
• Track their order/size
• Reassemble them
• Identify the resulting media/container format
• Export the reconstructed data when possible

It seems like Network DevTools gets you close, but .blob/MSE-based streaming makes it surprisingly difficult to get back to the actual resource.

Has anyone already built something like this?

Or is there some fundamental browser/MSE limitation that makes this approach impractical?

GPT and Claude is what I used through pwn college to help me learn instead of bothering people I could just ask deep questions and learn at anytime of day. Now they heavily restrict even the slightest hint of binary exploitation / RE conversations. Anyone here have success with another AI platform for learning?

A formatter, minifier or deobfuscator can be made to turn one script into another.

You can go try out all 186 techniques with this script: https://divergence.trustsig.eu/

Or try the Tetris-Snake demo here: https://divergence-game.trustsig.eu/

Techical breakdown: https://trustsig.eu/blog/javascript-divergence/

Hi. To preface, I am not selling anything, and I am not suggesting to mindlessly use this tool.

I started initially using Claude to hunt on some programs, and from there built a harness so that I could work on an engagement for a long duration without losing progress, to make the process repeatable and high quality ( high quality submissions, final findings that can be trusted ), and several other things along the way.

Yes this is a AI created project, but from hundreds of hours and testing, and over 8 months. Yes you will find some weird Python code, and maybe some weird things in the prompts, its 80/20.

Please still review everything, you may have to have the Operator re-dispatch specific agents to re-verify things, or to QC the final submissions, human in the loop is so very important.

I have not added GLM 5.3, I know many people are starting to use it for black box engagements, I will be working on that soon.

Project - https://github.com/VigilOSS/Vigil

hi this is my research, https://github.com/mein-0/KnockGiga

To all the beginners and the "explorers" this is the way.....I had lost a lot of time searching for resources—Pico, Nightmare.....but finally this is what actually teaches the stuff

Also....pls do support me (I guess twitter is the last place where I can enter, considering the condition of the current market)

https://x.com/s0h0m_ch_/status/2111068178235445354

Are there any courses or programs you would recommend for learning malware development?

I have a coding assignment that includes coding exploits but no ai will code it for me. Any suggestions for how to get around it or an ai that will code it for me?

hello guys ,I m trying to learn Reverse engineering, is there a roadmap for it ?

As the title says, I'm looking for projects to contribute to. This way I would like to pivot from my current operational security job to binary.

Feel free to answer to this post or pm me.
Thank you.

Hypothetically, suppose you discover several reasonably critical vulnerabilities in systems belonging to different organisations. You develop working exploits that can be used to gain unauthorised access to restricted systems or data.

Assume you've successfully tested the exploits and confirmed that they work, but you haven't stolen, modified or destroyed any data, and you haven't used the access for anything malicious.

Now imagine a random buyer offers you a substantial amount of money for one of these exploits.

Have you already committed a crime simply by exploiting the vulnerability to gain unauthorised access, even if you haven't done anything further?

Is possessing and selling a working exploit itself illegal, or does it depend on the circumstances?

Could you face prison time for selling it, even if you never personally use it for malicious purposes?

If the buyer subsequently uses the exploit to attack the organisation, could you be held criminally liable?

Would it make a legal difference if you genuinely didn't know what the buyer intended to do with it?

This is a hypothetical scenario.

Hey guys,
Wanted to share a tool I've been using in my own reversing workflow:

I needed a straightforward way to pull decompilation, cross-references, and struct layouts out of IDA Pro and Ghidra from external Python scripts and CLI utilities without setting up heavy web servers or dealing with bloated RPC frameworks.
It’s just two standalone scripts (`ID_Server.py` for IDAPython and `Ghidra_Server.py` for Ghidra). Once running, you send plain text commands over local TCP and get back JSON

I have an ongoing static analysis project I'm writing in C++20.

It uses Zydis for instruction decoding, LIEF for binary parsing and wxWidgets for the UI.

A big help was learning that the .pdata section in PE64 contains the start and end address of every non-trivial function in the binary. Enabling it to support exception handling like VEH and SEH at runtime.

This comes with some useful unwind metadata like prologue information, stack allocation size, preserved registers, etc.

Combining this with recursive descent from entry point, IAT entry resolution and memory operands like strings and such has already made this project more useful.

Is there more PE64, static analysis relevant, metadata baked into the file structure? Some future candidates are gonna be RTTI, virtual function tables, and some other CRT specific machinery.

Thanks for any suggestions.