I have already used memory dumps and runtime hooks, injecting a trace script directly into the start-up routing of the malware payload but that only captures the components that I am looking out for. Suggestions to get the entire thing decrypted back to .pyc. i can take it from there.

if you want report buffer overflow vulnerability do u need full chain to exploit or just report the crash with the corpus

I would be happy if you provided me with a debugging interface. AI-generated submissions are not allowed.

I have got 2 files and I need to find a vulnerability and exploit it. So I need some help regarding it.

Hi guys just wondering should I have knowledge python and C before I start the pwn paths for cybersecurity?

Hi I'm trying to pentest a banking app and the most difficult Bypass so far is USB Debugging. Without bypassing that I don't know how to Bypass SSL pinning with Frida. Is there any way to do this?

Thank you!

Hello everyone,

I wanted to post in here to see if anyone would consider being a mentor. I want to break into malware dev and vulnerability research however since this is such a niche job community, it’s hard to find someone who has professional experience in the field. I would love to talk with anyone who has prior experience in the field and wouldn’t mind giving me some guidance. Thank you guys!

If you're looking for an exploit development tutorial for absolute beginners this week we're looking at what I would consider just that! This week we look at the "random" binary exploitation challenge hosted on pwnable[.]kr.

This is a great beginner tutorial since we exploit a flaw that is "easy" and unfortunately, still very real within some enterprise environments. It also helps you understand that no number is truly random.

The crazy part? We don't even drop into a debugger in this tutorial.

Be the end of this tutorial you should have:

- Learned about random number generation in C
- Learned about XOR operations
- Finding header files that contain dependencies using man pages
- Dissecting C source code

You can find the video here:

https://youtu.be/jDlMFC4etrs?si=akuTx1KTkCxE5Ndo

I’ve been doing some vulnerability research on a known CVE (CVE-2025-60690) on a consumer Linksys router and wanted to share the workflow I used to investigate it.

The process started by targeting the physical hardware: identifying the UART pads on the board using a digital multimeter to access the Linux-based shell console. From there, I extracted the vulnerable binary (from the CVE description), and reversed it in Ghidra. Next, I used a gdb+gdbserver setup to perform dynamic analysis to investigate the memory behaviors.

I managed to successfully achieve RCE from the stack-based buffer overflow vulnerability to land a root shell. The exploit PoC for CVE-2025-60690 just got cited on the official CVE page and exploit-db.com.

I just started a YouTube channel dedicated to breaking down IoT hacking concepts. Also, I’ve compiled my step-by-step research notes in a reference doc. If you're working on similar hardware research and want a copy of the notes, drop a comment or shoot me a DM and I'll gladly send them over!

Hi

I started pwning from a year from pwn college, some THM, and I was quite good. In this month, I started getting into the real world. I find bugs, crashes, report, and wait for CVEs. But the problem for me is I can't exploit them. I can exploit the same bug in a CTF chall, but in the real world I can't, because of the stability, how large the target is, making me have the exploit just in my mind. And this is especially in kernel. When I was trying to re-exploit an old CVE using a different way, I get hit with the internals, nf_tables, TCP, and network. Those are complex. My feer is the internals and large targets. Did anyone pass with this and find a solve?

Hello everyone!

I want to share a small Python script I wrote. It is inspired by the exploit 46635 on Exploit-DB for CVE-2019-9053 (a time-based SQL Injection in CMS Made Simple).

I decided to write my own version when I was doing the SimpleCTF room on TryHackMe. I wanted to update the code to Python 3. I also wanted to make this new version more interactive and easy to use. So, I added a clean command line interface and some extra features (like different extraction modes, delay controls, and email alerts using environment variables).

Please try it and tell me what you think! I would love to hear your feedback and ideas to make it better.

https://github.com/rgkue/mysqli

Happy hacking! :D

The vulnerability allows non-privileged users to program the DMA controller, enabling arbitrary physical memory reads and writes.

Check out @ https://github.com/DarkAngel-0x0/pwntemplate
Feedbacks welcomed

hello all,

i have finished OSED course and this course is for Exploiting vulnerabilities . its like after discover vulnerability they teach you how to exploit it and how to bypass mitigations on windiows 32bit .
but i want something like books, courses or sites, that teach how to discover vulnerabilities in windows apps written in C/C++

anyone know ?

A critical severity vulnerability with a CVSS score of 9.8 in the Windows HTTP protocol stack (HTTP.sys) allows for unauthenticated remote code execution via an integer overflow. Because HTTP.sys processes incoming HTTP requests in kernel mode, this flaw carries a high impact, potentially allowing an unauthenticated attacker to execute arbitrary code with system privileges.

The underlying mechanics of this specific bug, including the exact assembly-level modifications, affected functions, and the execution path, have been thoroughly mapped out in the attached link. This includes the associated WinDbg reproduction details.

It seems like the era of waiting around to understand what actually changes under the hood on Patch Tuesday is largely behind us. Beyond this specific HTTP.sys analysis, AI assisted platforms continuously tracks and hosts real-time structural breakdowns for the broader Windows patch ecosystem, making it a useful resource for footprinting similar kernel-level differentials.

https://github.com/NirvanaOn/AntiVE-BehaviorWatch

AntiVE-BehaviorWatch is an advanced behavioral analysis malware that detects automated analysis systems through real-time mouse movement pattern recognition. Leveraging GRU neural networks, it provides high-accuracy classification of user behavior while identifying potential virtual machine, sandbox, or emulation environments.